bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2022‒06‒26
23 papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh
  1. Multiplexed Quantitative Proteomic Profiling of Cancer Cells and Tissues Using Isobaric Labeling-Based Tags.
  2. Proteome profiling of cerebrospinal fluid reveals biomarker candidates for Parkinson's disease.
  3. Profiling the Regulation of Histone Methylation and Demethylation by Metabolites and Metals.
  4. Targeted Microchip Capillary Electrophoresis-Orbitrap Mass Spectrometry Metabolomics to Monitor Ovarian Cancer Progression.
  5. Single-Cell Proteomics: The Critical Role of Nanotechnology.
  6. A set of gene knockouts as a resource for global lipidomic changes.
  7. A ferroptosis defense mechanism mediated by glycerol-3-phosphate dehydrogenase 2 in mitochondria.
  8. Cancer cells depend on environmental lipids for proliferation when electron acceptors are limited.
  9. Investigating Mitotic Inheritance of Histone Posttranslational Modifications by Triple pSILAC Coupled to Nascent Chromatin Capture.
  10. Orchestrated Action of AMPK Activation and Combined VEGF/PD-1 Blockade with Lipid Metabolic Tunning as Multi-Target Therapeutics against Ovarian Cancers.
  11. Biofluid Metabolomics and Lipidomics of Mice Exposed to External Very High-Dose Rate Radiation.
  12. The Use of Seahorse XF Assays to Interrogate Real-Time Energy Metabolism in Cancer Cell Lines.
  13. Aβ1-42 peptide toxicity on neuronal cells: A lipidomic study.
  14. Identifying Specific Protein Interactors of Nucleosomes Carrying Methylated Histones Using Quantitative Mass Spectrometry.
  15. 29-plex tandem mass tag mass spectrometry enabling accurate quantification by interference correction.
  16. HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values.
  17. Oxidative stress from DGAT1 oncoprotein inhibition in melanoma suppresses tumor growth when ROS defenses are also breached.
  18. Quantitative Comparison of Statistical Methods for Analyzing Human Metabolomics Data.
  19. Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging Drosophila.
  20. Tumor Microenvironment: Lactic Acid Promotes Tumor Development.
  21. Proteomics for comprehensive characterization of extracellular vesicles in neurodegenerative disease.
  22. Culture of Adherent Cancer Cell Lines.
  23. An Improved Method to Quantify Short-Chain Fatty Acids in Biological Samples Using Gas Chromatography-Mass Spectrometry.
  1. Methods Mol Biol. 2022 ;2508 211-223
    Multiplexed Quantitative Proteomic Profiling of Cancer Cells and Tissues Using Isobaric Labeling-Based Tags.
    Mukhayyo Sultonova, Devanand M Pinto, J Patrick Murphy.
      Comparing cancer proteomes across many samples offers a window into cancer cell biology and may reveal new treatment options for specific subsets of cancer. Here we describe a method using tandem mass tag (TMT) technology to multiplex up to 18 samples in a single analysis, paving the way for the analysis of large cohorts of tumors, cell lines, and perturbations thereof. The procedure we describe will result in samples ready for in-depth LC-MS/MS analysis in 3-4 days.
    Keywords:  Isobaric labeling; LC-MS/MS; Proteomic profiling; SP3
    DOI:  https://doi.org/10.1007/978-1-0716-2376-3_16
  2. Cell Rep Med. 2022 Jun 21. pii: S2666-3791(22)00193-8. [Epub ahead of print]3(6): 100661
    Proteome profiling of cerebrospinal fluid reveals biomarker candidates for Parkinson's disease.
    Ozge Karayel, Sebastian Virreira Winter, Shalini Padmanabhan, Yuliya I Kuras, Duc Tung Vu, Idil Tuncali, Kalpana Merchant, Anne-Marie Wills, Clemens R Scherzer, Matthias Mann.
      Parkinson's disease (PD) is a growing burden worldwide, and there is no reliable biomarker used in clinical routines to date. Cerebrospinal fluid (CSF) is routinely collected in patients with neurological symptoms and should closely reflect alterations in PD patients' brains. Here, we describe a scalable and sensitive mass spectrometry (MS)-based proteomics workflow for CSF proteome profiling. From two independent cohorts with over 200 individuals, our workflow reproducibly quantifies over 1,700 proteins from minimal CSF amounts. Machine learning determines OMD, CD44, VGF, PRL, and MAN2B1 to be altered in PD patients or to significantly correlate with clinical scores. We also uncover signatures of enhanced neuroinflammation in LRRK2 G2019S carriers, as indicated by increased levels of CTSS, PLD4, and HLA proteins. A comparison with our previously acquired urinary proteomes reveals a large overlap in PD-associated changes, including lysosomal proteins, opening up new avenues to improve our understanding of PD pathogenesis.
    Keywords:  CSF; DIA; LRRK2; Parkinson’s disease; biomarker; mass spectrometry; proteomics
    DOI:  https://doi.org/10.1016/j.xcrm.2022.100661
  3. Methods Mol Biol. 2022 ;2529 121-133
    Profiling the Regulation of Histone Methylation and Demethylation by Metabolites and Metals.
    Sebastian Müller, Fabien Sindikubwabo, Tatiana Cañeque, Raphaël Rodriguez.
      Here we describe how to profile the contribution of metabolism and implication of metals to histone methylation and demethylation. The techniques described with the adequate protocols are metabolomics, quantitative proteomics, inductively coupled mass spectrometry and nanoscale secondary ion mass spectrometry.
    Keywords:  Histone demethylation; Histone methylation; ICP-MS; Metabolomics; Metals; NanoSIMS; Proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2481-4_6
  4. Metabolites. 2022 Jun 09. pii: 532. [Epub ahead of print]12(6):
    Targeted Microchip Capillary Electrophoresis-Orbitrap Mass Spectrometry Metabolomics to Monitor Ovarian Cancer Progression.
    Samyukta Sah, Sylvia R Yun, David A Gaul, Andro Botros, Eun Young Park, Olga Kim, Jaeyeon Kim, Facundo M Fernández.
      The lack of effective screening strategies for high-grade serous carcinoma (HGSC), a subtype of ovarian cancer (OC) responsible for 70-80% of OC related deaths, emphasizes the need for new diagnostic markers and a better understanding of disease pathogenesis. Capillary electrophoresis (CE) coupled with high-resolution mass spectrometry (HRMS) offers high selectivity and sensitivity for ionic compounds, thereby enhancing biomarker discovery. Recent advances in CE-MS include small, chip-based CE systems coupled with nanoelectrospray ionization (nanoESI) to provide rapid, high-resolution analysis of biological specimens. Here, we describe the development of a targeted microchip (µ) CE-HRMS method, with an acquisition time of only 3 min and sample injection volume of 4nL, to analyze 40 target metabolites in serum samples from a triple-mutant (TKO) mouse model of HGSC. Extracted ion electropherograms showed sharp, baseline resolved peak shapes, even for structural isomers such as leucine and isoleucine. All calibration curves of the analytes maintained good linearity with an average R2 of 0.994, while detection limits were in the nM range. Thirty metabolites were detected in mouse serum with recoveries ranging from 78 to 120%, indicating minimal ionization suppression and good accuracy. We applied the µCE-HRMS method to biweekly-collected serum samples from TKO and TKO control mice. A time-resolved analysis revealed characteristic temporal trends for amino acids, nucleosides, and amino acid derivatives. These metabolic alterations are indicative of altered nucleotide biosynthesis and amino acid metabolism in HGSC development and progression. A comparison of the µCE-HRMS dataset with non-targeted ultra-high performance liquid chromatography (UHPLC)-MS results showed identical temporal trends for the five metabolites detected with both platforms, indicating the µCE-HRMS method performed satisfactorily in terms of capturing metabolic reprogramming due to HGSC progression while reducing the total data collection time three-fold.
    Keywords:  high-grade serous ovarian cancer; mass spectrometry; microchip capillary electrophoresis
    DOI:  https://doi.org/10.3390/metabo12060532
  5. Int J Mol Sci. 2022 Jun 16. pii: 6707. [Epub ahead of print]23(12):
    Single-Cell Proteomics: The Critical Role of Nanotechnology.
    Carlota Arias-Hidalgo, Pablo Juanes-Velasco, Alicia Landeira-Viñuela, Marina L García-Vaquero, Enrique Montalvillo, Rafael Góngora, Ángela-Patricia Hernández, Manuel Fuentes.
      In single-cell analysis, biological variability can be attributed to individual cells, their specific state, and the ability to respond to external stimuli, which are determined by protein abundance and their relative alterations. Mass spectrometry (MS)-based proteomics (e.g., SCoPE-MS and SCoPE2) can be used as a non-targeted method to detect molecules across hundreds of individual cells. To achieve high-throughput investigation, novel approaches in Single-Cell Proteomics (SCP) are needed to identify and quantify proteins as accurately as possible. Controlling sample preparation prior to LC-MS analysis is critical, as it influences sensitivity, robustness, and reproducibility. Several nanotechnological approaches have been developed for the removal of cellular debris, salts, and detergents, and to facilitate systematic sample processing at the nano- and microfluidic scale. In addition, nanotechnology has enabled high-throughput proteomics analysis, which have required the improvement of software tools, such as DART-ID or DO-MS, which are also fundamental for addressing key biological questions. Single-cell proteomics has many applications in nanomedicine and biomedical research, including advanced cancer immunotherapies or biomarker characterization, among others; and novel methods allow the quantification of more than a thousand proteins while analyzing hundreds of single cells.
    Keywords:  antibodies; biological variability; cancer immunotherapy; clinical research; mass-spectrometry; nanotechnology; single-cell proteomics
    DOI:  https://doi.org/10.3390/ijms23126707
  6. Sci Rep. 2022 Jun 22. 12(1): 10533
    A set of gene knockouts as a resource for global lipidomic changes.
    Aleksandra Spiegel, Chris Lauber, Mandy Bachmann, Anne-Kristin Heninger, Christian Klose, Kai Simons, Mihail Sarov, Mathias J Gerl.
      Enzyme specificity in lipid metabolic pathways often remains unresolved at the lipid species level, which is needed to link lipidomic molecular phenotypes with their protein counterparts to construct functional pathway maps. We created lipidomic profiles of 23 gene knockouts in a proof-of-concept study based on a CRISPR/Cas9 knockout screen in mammalian cells. This results in a lipidomic resource across 24 lipid classes. We highlight lipid species phenotypes of multiple knockout cell lines compared to a control, created by targeting the human safe-harbor locus AAVS1 using up to 1228 lipid species and subspecies, charting lipid metabolism at the molecular level. Lipid species changes are found in all knockout cell lines, however, some are most apparent on the lipid class level (e.g., SGMS1 and CEPT1), while others are most apparent on the fatty acid level (e.g., DECR2 and ACOT7). We find lipidomic phenotypes to be reproducible across different clones of the same knockout and we observed similar phenotypes when two enzymes that catalyze subsequent steps of the long-chain fatty acid elongation cycle were targeted.
    DOI:  https://doi.org/10.1038/s41598-022-14690-0
  7. Proc Natl Acad Sci U S A. 2022 Jun 28. 119(26): e2121987119
    A ferroptosis defense mechanism mediated by glycerol-3-phosphate dehydrogenase 2 in mitochondria.
    Shiqi Wu, Chao Mao, Lavanya Kondiparthi, Masha V Poyurovsky, Kellen Olszewski, Boyi Gan.
      Mechanisms of defense against ferroptosis (an iron-dependent form of cell death induced by lipid peroxidation) in cellular organelles remain poorly understood, hindering our ability to target ferroptosis in disease treatment. In this study, metabolomic analyses revealed that treatment of cancer cells with glutathione peroxidase 4 (GPX4) inhibitors results in intracellular glycerol-3-phosphate (G3P) depletion. We further showed that supplementation of cancer cells with G3P attenuates ferroptosis induced by GPX4 inhibitors in a G3P dehydrogenase 2 (GPD2)-dependent manner; GPD2 deletion sensitizes cancer cells to GPX4 inhibition-induced mitochondrial lipid peroxidation and ferroptosis, and combined deletion of GPX4 and GPD2 synergistically suppresses tumor growth by inducing ferroptosis in vivo. Mechanistically, inner mitochondrial membrane-localized GPD2 couples G3P oxidation with ubiquinone reduction to ubiquinol, which acts as a radical-trapping antioxidant to suppress ferroptosis in mitochondria. Taken together, these results reveal that GPD2 participates in ferroptosis defense in mitochondria by generating ubiquinol.
    Keywords:  GPD2; cell death; ferroptosis; lipid peroxidation; mitochondria
    DOI:  https://doi.org/10.1073/pnas.2121987119
  8. Nat Metab. 2022 Jun 23.
    Cancer cells depend on environmental lipids for proliferation when electron acceptors are limited.
    Zhaoqi Li, Brian W Ji, Purushottam D Dixit, Konstantine Tchourine, Evan C Lien, Aaron M Hosios, Keene L Abbott, Justine C Rutter, Anna M Westermark, Elizabeth F Gorodetsky, Lucas B Sullivan, Matthew G Vander Heiden, Dennis Vitkup.
      Production of oxidized biomass, which requires regeneration of the cofactor NAD+, can be a proliferation bottleneck that is influenced by environmental conditions. However, a comprehensive quantitative understanding of metabolic processes that may be affected by NAD+ deficiency is currently missing. Here, we show that de novo lipid biosynthesis can impose a substantial NAD+ consumption cost in proliferating cancer cells. When electron acceptors are limited, environmental lipids become crucial for proliferation because NAD+ is required to generate precursors for fatty acid biosynthesis. We find that both oxidative and even net reductive pathways for lipogenic citrate synthesis are gated by reactions that depend on NAD+ availability. We also show that access to acetate can relieve lipid auxotrophy by bypassing the NAD+ consuming reactions. Gene expression analysis demonstrates that lipid biosynthesis strongly anti-correlates with expression of hypoxia markers across tumor types. Overall, our results define a requirement for oxidative metabolism to support biosynthetic reactions and provide a mechanistic explanation for cancer cell dependence on lipid uptake in electron acceptor-limited conditions, such as hypoxia.
    DOI:  https://doi.org/10.1038/s42255-022-00588-8
  9. Methods Mol Biol. 2022 ;2529 407-417
    Investigating Mitotic Inheritance of Histone Posttranslational Modifications by Triple pSILAC Coupled to Nascent Chromatin Capture.
    Kyosuke Nakamura, Anja Groth, Constance Alabert.
      Pulse stable isotope labeling with amino acids in cell culture (pSILAC) coupled to mass spectrometric analysis is a powerful tool to study propagation of histone post-translational modifications (PTMs). We describe the combination of triple pSILAC with pulse-chase labeling of newly replicated DNA by nascent chromatin capture (NCC). This technology tracks newly synthesized and recycled old histones, from deposition to transmission to daughter cells, unveiling principles of histone-based inheritance.
    Keywords:  Chromatin assembly; DNA replication; Histone; Mass spectrometry; Nascent Chromatin Capture; Posttranslational modifications; Pulse-chase; SILAC
    DOI:  https://doi.org/10.1007/978-1-0716-2481-4_17
  10. Int J Mol Sci. 2022 Jun 20. pii: 6857. [Epub ahead of print]23(12):
    Orchestrated Action of AMPK Activation and Combined VEGF/PD-1 Blockade with Lipid Metabolic Tunning as Multi-Target Therapeutics against Ovarian Cancers.
    Mingo M H Yung, Michelle K Y Siu, Hextan Y S Ngan, David W Chan, Karen K L Chan.
      Ovarian cancer is one of the most lethal gynecological malignancies worldwide, and chemoresistance is a critical obstacle in the clinical management of the disease. Recent studies have suggested that exploiting cancer cell metabolism by applying AMP-activated protein kinase (AMPK)-activating agents and distinctive adjuvant targeted therapies can be a plausible alternative approach in cancer treatment. Therefore, the perspectives about the combination of AMPK activators together with VEGF/PD-1 blockade as a dual-targeted therapy against ovarian cancer were discussed herein. Additionally, ferroptosis, a non-apoptotic regulated cell death triggered by the availability of redox-active iron, have been proposed to be governed by multiple layers of metabolic signalings and can be synergized with immunotherapies. To this end, ferroptosis initiating therapies (FITs) and metabolic rewiring and immunotherapeutic approaches may have substantial clinical potential in combating ovarian cancer development and progression. It is hoped that the viewpoints deliberated in this review would accelerate the translation of remedial concepts into clinical trials and improve the effectiveness of ovarian cancer treatment.
    Keywords:  AMPK; PD-1 blockade; VEGF; cancer metabolism; ferroptosis; ovarian cancer; polyunsaturated fatty acids; tumor microenvironment
    DOI:  https://doi.org/10.3390/ijms23126857
  11. Metabolites. 2022 Jun 04. pii: 520. [Epub ahead of print]12(6):
    Biofluid Metabolomics and Lipidomics of Mice Exposed to External Very High-Dose Rate Radiation.
    Evan L Pannkuk, Evagelia C Laiakis, Guy Garty, Shivani Bansal, Brian Ponnaiya, Xuefeng Wu, Shanaz A Ghandhi, Sally A Amundson, David J Brenner, Albert J Fornace.
      High-throughput biodosimetry methods to determine exposure to ionizing radiation (IR) that can also be easily scaled to multiple testing sites in emergency situations are needed in the event of malicious attacks or nuclear accidents that may involve a substantial number of civilians. In the event of an improvised nuclear device (IND), a complex IR exposure will have a very high-dose rate (VHDR) component from an initial blast. We have previously addressed low-dose rate (LDR, ≤1 Gy/day) exposures from internal emitters on biofluid small molecule signatures, but further research on the VHDR component of the initial blast is required. Here, we exposed 8- to 10-week-old male C57BL/6 mice to an acute dose of 3 Gy using a reference dose rate of 0.7 Gy/min or a VHDR of 7 Gy/s, collected urine and serum at 1 and 7 d, then compared the metabolite signatures using either untargeted (urine) or targeted (serum) approaches with liquid chromatography mass spectrometry platforms. A Random Forest classification approach showed strikingly similar changes in urinary signatures at 1 d post-irradiation with VHDR samples grouping closer to control samples at 7 d. Identical metabolite panels (carnitine, trigonelline, xanthurenic acid, N6,N6,N6-trimethyllysine, spermine, and hexosamine-valine-isoleucine-OH) could differentiate IR exposed individuals with high sensitivity and specificity (area under the receiver operating characteristic (AUROC) curves 0.89-1.00) irrespective of dose rate at both days. For serum, the top 25 significant lipids affected by IR exposure showed slightly higher perturbations at 0.7 Gy/min vs. 7 Gy/s; however, identical panels showed excellent sensitivity and specificity at 1 d (three hexosylceramides (16:0), (18:0), (24:0), sphingomyelin [26:1], lysophosphatidylethanolamine [22:1]). Mice could not be differentiated from control samples at 7 d for a 3 Gy exposure based on serum lipid signatures. As with LDR exposures, we found that identical biofluid small molecule signatures can identify IR exposed individuals irrespective of dose rate, which shows promise for more universal applications of metabolomics for biodosimetry.
    Keywords:  biodosimetry; ionizing radiation; lipidomics; mass spectrometry; metabolomics; very high-dose rate
    DOI:  https://doi.org/10.3390/metabo12060520
  12. Methods Mol Biol. 2022 ;2508 225-234
    The Use of Seahorse XF Assays to Interrogate Real-Time Energy Metabolism in Cancer Cell Lines.
    Jenna K Caines, David A Barnes, Mark D Berry.
      The propensity of cancer cells to preferentially undergo anaerobic metabolism despite oxygen being abundant is referred to as the Warburg effect. Measuring cellular metabolism is therefore central to understanding the cellular physiology of cancer cells. The Seahorse XFe Analyzer series allows real-time measurement of cellular metabolism. In the basic assay, two parameters, the oxygen consumption rate (OCR) and the extracellular acidification rate (ECAR), are used to determine real-time changes in the energy needs of live cells: OCR provides a measure of aerobic mitochondrial respiration; ECAR gives a measure of anaerobic glycolysis. Through the use of various respiration inhibitors, the Seahorse assay allows baseline respiration rate and total aerobic and anaerobic ATP production to be determined under a variety of experimental conditions. Here we describe the protocol for completing the Seahorse Real-Time ATP Rate Assay for adherent and suspension cancer cell lines. Depending on individual experimental results, more refined subsequent assays can then be performed to specifically determine, for example, the ability to utilize different substrates by the cell lines in the presence and absence of pharmacological and/or genetic interventions.
    Keywords:  ATP; Cancer cell metabolism; Energy metabolism; Glycolysis; Mitochondria; Seahorse
    DOI:  https://doi.org/10.1007/978-1-0716-2376-3_17
  13. J Pharm Biomed Anal. 2022 Jun 06. pii: S0731-7085(22)00297-7. [Epub ahead of print]219 114876
    Aβ1-42 peptide toxicity on neuronal cells: A lipidomic study.
    Lara Davani, Xiaoqing Fu, Angela De Simone, Peng Li, Serena Montanari, Michael Lämmerhofer, Vincenza Andrisano.
      Currently Alzheimer's Disease (AD) pathological pathways, which lead to cell death and dementia, are not completely well-defined; in particular, the lipid changes in brain tissues that begin years before AD symptoms. Due to the central role of the amyloid aggregation process in the early phase of AD pathogenesis, we aimed at developing a lipidomic approach to evaluate the amyloid toxic effects on differentiated human neuroblastoma derived SH-SY5Y cells. First of all, this work was performed to highlight qualitative and relative quantitative lipid variations in connection with amyloid toxicity. Then, with an open outcome, the study was focused to find out some new lipid-based biomarkers that could result from the interaction of amyloid peptide with cell membrane and could justify neuroblastoma cells neurotoxicity. Hence, cells were treated with increasing concentration of Aβ1-42 at different times, then the lipid extraction was carried out by protein precipitation protocol with 2-propanol-water (90:10 v/v). The LC-MS analysis of samples was performed by a RP-UHPLC system coupled with a quadrupole-time-of-flight mass spectrometer in comprehensive data - independent SWATH acquisition mode. Data processing was achieved by MS-DIAL. Each lipid class profile in SH-SY5Y cells treated with Aβ1-42 was compared to the one obtained for the untreated cells to identify (and relatively quantify) some altered species in various lipid classes. This approach was found suitable to underline some peculiar lipid alterations that might be correlated to different Aβ1-42 aggregation species and to explore the cellular response mechanisms to the toxic stimuli. The in vitro model presented has provided results that coincide with the ones in literature obtained by lipidomic analysis on cerebrospinal fluid and plasma of AD patients. Therefore, after being validated, this method could represent a way for the preliminary identification of potential biomarkers that could be researched in biological samples of AD patients.
    Keywords:  Alzheimer’s disease; Amyloid toxicity; Biomarkers; Lipids; Mass spectrometry
    DOI:  https://doi.org/10.1016/j.jpba.2022.114876
  14. Methods Mol Biol. 2022 ;2529 327-403
    Identifying Specific Protein Interactors of Nucleosomes Carrying Methylated Histones Using Quantitative Mass Spectrometry.
    Andrey Tvardovskiy, Nhuong Nguyen, Till Bartke.
      Chemical modification of histone proteins by methylation plays a central role in chromatin regulation by recruiting epigenetic "readers" via specialized binding domains. Depending on the degree of methylation, the exact modified amino acid, and the associated reader proteins histone methylations are involved in the regulation of all DNA-based processes, such as transcription, DNA replication, and DNA repair. Here we present methods to identify histone methylation readers using a mass spectrometry-linked nucleosome affinity purification approach. We provide detailed protocols for the generation of semisynthetic methylated histones, their assembly into biotinylated nucleosomes, and the identification of methylation-specific nucleosome-interacting proteins from nuclear extracts via nucleosome pull-downs and label-free quantitative proteomics. Due to their versatility, these protocols allow the identification of readers of various histone methylations, and can also be adapted to different cell types and tissues, and other types of modifications.
    Keywords:  Affinity purification; Chromatin; Histone; Histone modification; Mass spectrometry; Methylation; Native chemical ligation; Nuclear extract; Nucleosome; Proteomics
    DOI:  https://doi.org/10.1007/978-1-0716-2481-4_16
  15. Proteomics. 2022 Jun 20. e2100243
    29-plex tandem mass tag mass spectrometry enabling accurate quantification by interference correction.
    Huan Sun, Suresh Poudel, David Vanderwall, Dong Geun Lee, Yuxin Li, Junmin Peng.
      Tandem mass tag (TMT) mass spectrometry is a mainstream isobaric chemical labeling strategy for profiling proteomes. Here we present a 29-plex TMT method to combine the 11-plex and 18-plex labeling strategies. The 29-plex method was examined with a pooled sample composed of 1x, 3x and 10x E. coli peptides with 100x human background peptides, which generated two E. coli datasets (TMT11 and TMT18), displaying the distorted ratios of 1.0:1.7:4.2 and 1.0:1.8:4.9, respectively. This ratio compression from the expected 1:3:10 ratios was caused by co-isolated TMT-labeled ions (i.e., noise). Interestingly, the mixture of two TMT sets produced MS/MS spectra with unique features for the noise detection: (i) in TMT11-labeled spectra, TMT18-specific reporter ions (e.g., 135N) were shown as the noise; (ii) in TMT18-labeled spectra, the TMT11/TMT18-shared reporter ions (e.g., 131C) typically exhibited higher intensities than TMT18-specific reporter ions, due to contaminated TMT11-labeled ions in these shared channels. We further estimated the noise levels contributed by both TMT11- and TMT18-labeled peptides, and corrected reporter ion intensities in every spectrum. Finally, the anticipated 1:3:10 ratios were largely restored. This strategy was also validated using another 29-plex sample with 1:5 ratios. Thus the 29-plex method expands the TMT throughput and enhances the quantitative accuracy. This article is protected by copyright. All rights reserved.
    Keywords:  data processing; interference; liquid chromatography; mass spectrometry; proteome; proteomics; ratio compression; tandem mass tag
    DOI:  https://doi.org/10.1002/pmic.202100243
  16. Nat Commun. 2022 Jun 20. 13(1): 3523
    HarmonizR enables data harmonization across independent proteomic datasets with appropriate handling of missing values.
    Hannah Voß, Simon Schlumbohm, Philip Barwikowski, Marcus Wurlitzer, Matthias Dottermusch, Philipp Neumann, Hartmut Schlüter, Julia E Neumann, Christoph Krisp.
      Dataset integration is common practice to overcome limitations in statistically underpowered omics datasets. Proteome datasets display high technical variability and frequent missing values. Sophisticated strategies for batch effect reduction are lacking or rely on error-prone data imputation. Here we introduce HarmonizR, a data harmonization tool with appropriate missing value handling. The method exploits the structure of available data and matrix dissection for minimal data loss, without data imputation. This strategy implements two common batch effect reduction methods-ComBat and limma (removeBatchEffect()). The HarmonizR strategy, evaluated on four exemplarily analyzed datasets with up to 23 batches, demonstrated successful data harmonization for different tissue preservation techniques, LC-MS/MS instrumentation setups, and quantification approaches. Compared to data imputation methods, HarmonizR was more efficient and performed superior regarding the detection of significant proteins. HarmonizR is an efficient tool for missing data tolerant experimental variance reduction and is easily adjustable for individual dataset properties and user preferences.
    DOI:  https://doi.org/10.1038/s41467-022-31007-x
  17. Cell Rep. 2022 Jun 21. pii: S2211-1247(22)00781-1. [Epub ahead of print]39(12): 110995
    Oxidative stress from DGAT1 oncoprotein inhibition in melanoma suppresses tumor growth when ROS defenses are also breached.
    Daniel J Wilcock, Andrew P Badrock, Chun W Wong, Rhys Owen, Melissa Guerin, Andrew D Southam, Hannah Johnston, Brian A Telfer, Paul Fullwood, Joanne Watson, Harriet Ferguson, Jennifer Ferguson, Gavin R Lloyd, Andris Jankevics, Warwick B Dunn, Claudia Wellbrock, Paul Lorigan, Craig Ceol, Chiara Francavilla, Michael P Smith, Adam F L Hurlstone.
      Dysregulated cellular metabolism is a cancer hallmark for which few druggable oncoprotein targets have been identified. Increased fatty acid (FA) acquisition allows cancer cells to meet their heightened membrane biogenesis, bioenergy, and signaling needs. Excess FAs are toxic to non-transformed cells but surprisingly not to cancer cells. Molecules underlying this cancer adaptation may provide alternative drug targets. Here, we demonstrate that diacylglycerol O-acyltransferase 1 (DGAT1), an enzyme integral to triacylglyceride synthesis and lipid droplet formation, is frequently up-regulated in melanoma, allowing melanoma cells to tolerate excess FA. DGAT1 over-expression alone transforms p53-mutant zebrafish melanocytes and co-operates with oncogenic BRAF or NRAS for more rapid melanoma formation. Antagonism of DGAT1 induces oxidative stress in melanoma cells, which adapt by up-regulating cellular reactive oxygen species defenses. We show that inhibiting both DGAT1 and superoxide dismutase 1 profoundly suppress tumor growth through eliciting intolerable oxidative stress.
    Keywords:  CP: Cancer; DGAT1; SOD1; fatty acids; lipid droplets; melanoma; oxidative stress; reactive oxygen species
    DOI:  https://doi.org/10.1016/j.celrep.2022.110995
  18. Metabolites. 2022 Jun 04. pii: 519. [Epub ahead of print]12(6):
    Quantitative Comparison of Statistical Methods for Analyzing Human Metabolomics Data.
    Mir Henglin, Brian L Claggett, Joseph Antonelli, Mona Alotaibi, Gino Alberto Magalang, Jeramie D Watrous, Kim A Lagerborg, Gavin Ovsak, Gabriel Musso, Olga V Demler, Ramachandran S Vasan, Martin G Larson, Mohit Jain, Susan Cheng.
      Emerging technologies now allow for mass spectrometry-based profiling of thousands of small molecule metabolites ('metabolomics') in an increasing number of biosamples. While offering great promise for insight into the pathogenesis of human disease, standard approaches have not yet been established for statistically analyzing increasingly complex, high-dimensional human metabolomics data in relation to clinical phenotypes, including disease outcomes. To determine optimal approaches for analysis, we formally compare traditional and newer statistical learning methods across a range of metabolomics dataset types. In simulated and experimental metabolomics data derived from large population-based human cohorts, we observe that with an increasing number of study subjects, univariate compared to multivariate methods result in an apparently higher false discovery rate as represented by substantial correlation between metabolites directly associated with the outcome and metabolites not associated with the outcome. Although the higher frequency of such associations would not be considered false in the strict statistical sense, it may be considered biologically less informative. In scenarios wherein the number of assayed metabolites increases, as in measures of nontargeted versus targeted metabolomics, multivariate methods performed especially favorably across a range of statistical operating characteristics. In nontargeted metabolomics datasets that included thousands of metabolite measures, sparse multivariate models demonstrated greater selectivity and lower potential for spurious relationships. When the number of metabolites was similar to or exceeded the number of study subjects, as is common with nontargeted metabolomics analysis of relatively small cohorts, sparse multivariate models exhibited the most-robust statistical power with more consistent results. These findings have important implications for metabolomics analysis in human disease.
    Keywords:  metabolomics; multivariate; statistical methods; univariate
    DOI:  https://doi.org/10.3390/metabo12060519
  19. Nat Commun. 2022 Jun 20. 13(1): 3518
    Global stable-isotope tracing metabolomics reveals system-wide metabolic alternations in aging Drosophila.
    Ruohong Wang, Yandong Yin, Jingshu Li, Hongmiao Wang, Wanting Lv, Yang Gao, Tangci Wang, Yedan Zhong, Zhiwei Zhou, Yuping Cai, Xiaoyang Su, Nan Liu, Zheng-Jiang Zhu.
      System-wide metabolic homeostasis is crucial for maintaining physiological functions of living organisms. Stable-isotope tracing metabolomics allows to unravel metabolic activity quantitatively by measuring the isotopically labeled metabolites, but has been largely restricted by coverage. Delineating system-wide metabolic homeostasis at the whole-organism level remains challenging. Here, we develop a global isotope tracing metabolomics technology to measure labeled metabolites with a metabolome-wide coverage. Using Drosophila as an aging model organism, we probe the in vivo tracing kinetics with quantitative information on labeling patterns, extents and rates on a metabolome-wide scale. We curate a system-wide metabolic network to characterize metabolic homeostasis and disclose a system-wide loss of metabolic coordinations that impacts both intra- and inter-tissue metabolic homeostasis significantly during Drosophila aging. Importantly, we reveal an unappreciated metabolic diversion from glycolysis to serine metabolism and purine metabolism as Drosophila aging. The developed technology facilitates a system-level understanding of metabolic regulation in living organisms.
    DOI:  https://doi.org/10.1038/s41467-022-31268-6
  20. J Immunol Res. 2022 ;2022 3119375
    Tumor Microenvironment: Lactic Acid Promotes Tumor Development.
    Yuting Gao, Hao Zhou, Gege Liu, Junlu Wu, Yi Yuan, Anquan Shang.
      Lactic acid is a "metabolic waste" product of glycolysis that is produced in the body. However, the role of lactic acid in the development of human malignancies has gained increasing interest lately as a multifunctional small molecule chemical. There is evidence that tumor cells may create a large amount of lactic acid through glycolysis even when they have abundant oxygen. Tumor tissues have a higher quantity of lactic acid than normal tissues. Lactic acid is required for tumor development. Lactate is an immunomodulatory chemical that affects both innate and adaptive immune cells' effector functions. In immune cells, the lactate signaling pathway may potentially serve as a link between metabolism and immunity. Lactate homeostasis is significantly disrupted in the TME. Lactate accumulation results in acidosis, angiogenesis, immunosuppression, and tumor cell proliferation and survival, all of which are deleterious to health. Thus, augmenting anticancer immune responses by lactate metabolism inhibition may modify lactate levels in the tumor microenvironment. This review will evaluate the role of lactic acid in tumor formation, metastasis, prognosis, treatment, and histone modification. Our findings will be of considerable interest to readers, particularly those engaged in the therapeutic treatment of cancer patients. Treatments targeting the inhibition of lactate synthesis and blocking the source of lactate have emerged as a potential new therapeutic option for oncology patients. Additionally, lactic acid levels in the plasma may serve as biomarkers for disease stage and may be beneficial for evaluating therapy effectiveness in individuals with tumors.
    DOI:  https://doi.org/10.1155/2022/3119375
  21. Exp Neurol. 2022 Jun 19. pii: S0014-4886(22)00174-1. [Epub ahead of print]355 114149
    Proteomics for comprehensive characterization of extracellular vesicles in neurodegenerative disease.
    Arada Vinaiphat, Siu Kwan Sze.
      Extracellular vesicles (EVs) are small lipid bilayer particles ubiquitously released by almost every cell type. A specific and selective constituents of EVs loaded with variety of proteins, lipids, small noncoding RNAs, and long non-coding RNAs are reflective of cellular events, type, and physiologic/pathophysiologic status of the cell of origin. Moreover, these molecular contents carry information from the cell of origin to recipient cells, modulating intercellular communication. Recent studies demonstrated that EVs not only play a neuroprotective role by mediating the removal of toxic proteins, but also emerge as an important player in various neurodegenerative disease onset and progression through facilitating of misfolded proteins propagation. For this reason, neurodegenerative disease-associated differences in EV proteome relative to normal EVs can be used to fulfil diagnostic, prognostic, and therapeutic purposes. Nonetheless, characterizing EV proteome obtained from biological samples (brain tissue and body fluids, including urea, blood, saliva, and CSF) is a challenging task. Herein, we review the status of EV proteome profiling and the updated discovery of potential biomarkers for the diagnosis of neurodegenerative disease with an emphasis on the integration of high-throughput advanced mass spectrometry (MS) technologies for both qualitative and quantitative analysis of EVs in different clinical tissue/body fluid samples in past five years.
    Keywords:  Biomarkers; Exosomes; Extracellular vesicles; Mass spectrometry; Neurodegenerative disease; Proteomics
    DOI:  https://doi.org/10.1016/j.expneurol.2022.114149
  22. Methods Mol Biol. 2022 ;2508 19-29
    Culture of Adherent Cancer Cell Lines.
    Vanessa Noel, Mark D Berry.
      Adherent cell lines grow attached to the surface of a cell culture vessel. Due to the adherent nature of the cells, enzymes, such as trypsin, are required to lift the cells from the cell culture vessel for harvesting or subculturing. Many cancer cell lines are adherent, rendering adherent cell culture a critical experimental method in the fields of cell biology, biochemistry, and cancer research. In this chapter, we outline the protocols for culturing and maintaining adherent cells. We detail the procedures for preparing cell culture medium, thawing and reviving frozen adherent cells, subculturing adherent cells, freezing cells, and counting cells. Most notably, we outline the best techniques and practices for optimal growth of healthy adherent cells while diminishing the risk of contamination.
    Keywords:  Adherent cell; Cancer; Cell culture; Cell line; Culture medium
    DOI:  https://doi.org/10.1007/978-1-0716-2376-3_3
  23. Metabolites. 2022 Jun 07. pii: 525. [Epub ahead of print]12(6):
    An Improved Method to Quantify Short-Chain Fatty Acids in Biological Samples Using Gas Chromatography-Mass Spectrometry.
    Kyeong-Seog Kim, Yujin Lee, Woori Chae, Joo-Youn Cho.
      Gut microbial metabolites, short-chain fatty acids (SCFAs), are found at multiple locations in the host body and are identified as important metabolites in gut microbiome-associated diseases. Quantifying SCFAs in diverse biological samples is important to understand their roles in host health. This study developed an accurate SCFA quantification method by performing gas chromatography-mass spectrometry (GC/MS) in human plasma, serum, feces, and mouse cecum tissue. The samples were acidified with hydrochloric acid, and the SCFAs were extracted using methyl tert-butyl ether. In this method, distilled water was selected as a surrogate matrix for the quantification of SCFAs in target biological samples. The method was validated in terms of linearity, parallelism, precision, recovery, and matrix effect. The developed method was further applied in target biological samples. In conclusion, this optimized method can be used as a simultaneous SCFA quantification method in diverse biological samples.
    Keywords:  GC/MS; cecum tissue; feces; plasma; serum; short-chain fatty acids; surrogate matrix
    DOI:  https://doi.org/10.3390/metabo12060525
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