bims-mascan Biomed News
on Mass spectrometry in cancer research
Issue of 2021‒06‒27
sixteen papers selected by
Giovanny Rodriguez Blanco
University of Edinburgh
  1. A merged method for targeted analysis of amino acids and derivatives using parallel reaction monitoring combined with untargeted profiling by HILIC-Q-Orbitrap HRMS.
  2. Ether phospholipids govern ferroptosis.
  3. Excess Polyunsaturated Fatty Acids Induce Death in Acidic Cancer Cells.
  4. Dynamic binning peak detection and assessment of various lipidomics liquid chromatography-mass spectrometry pre-processing platforms.
  5. KEAP1 deficiency drives glucose dependency and sensitizes lung cancer cells and tumors to GLUT inhibition.
  6. DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics.
  7. From bedside to bench-practical considerations to avoid pre-analytical pitfalls and assess sample quality for high-resolution metabolomics and lipidomics analyses of body fluids.
  8. Protocol for the processing and downstream analysis of phosphoproteomic data with PhosR.
  9. Comparative LC-MS/MS lipidomic analysis of macaque heart tissue flash frozen or embedded in optimal cutting temperature polymer (OCT): Practical considerations.
  10. Omics Untargeted Key Script: R-Based Software Toolbox for Untargeted Metabolomics with Bladder Cancer Biomarkers Discovery Case Study.
  11. Acoustic Mist Ionization Mass Spectrometry for Ultrahigh-Throughput Metabolomics Screening.
  12. Lipidomic and transcriptional analysis of the Linoleoyl-omega-Hydroxyceramide biosynthetic pathway in human psoriatic lesions.
  13. A Universal and High-Throughput Proteomics Sample Preparation Platform.
  14. A rapid, simple and sensitive microfluidic chip electrophoresis mass spectrometry method for monitoring amino acids in cell culture media.
  15. Histone acylations and chromatin dynamics: concepts, challenges, and links to metabolism.
  16. Plasmalogens - Ubiquitous molecules occurring widely, from anaerobic bacteria to humans.
  1. J Pharm Biomed Anal. 2021 Jun 15. pii: S0731-7085(21)00319-8. [Epub ahead of print]203 114208
    A merged method for targeted analysis of amino acids and derivatives using parallel reaction monitoring combined with untargeted profiling by HILIC-Q-Orbitrap HRMS.
    Lu Zhang, Wen Zheng, Xin Li, Shisheng Wang, Ming Xiao, Rui Xiao, Dingkun Zhang, Nengwen Ke, Huawei Cai, Jingqiu Cheng, Xiaolei Chen, Meng Gong.
      With continuously increased scan rate and sensitivity, high resolution mass spectrometry (HRMS) allows for both reliable targeted analysis (e.g., parallel reaction monitoring, PRM) and a global overview for discovery-based untargeted profiling (e.g., data dependent acquisition, DDA) to be performed. Based on previous study on PRM for large scale targeted metabolomics quantification, we developed an innovative method merged targeted and untargeted approaches in a single run. In our workflow, the scheduled PRM for targeted analysis of amino acids and derivatives combined with the full scan was acquired in every sample injection by hydrophilic interaction liquid chromatography tandem quadrupole-Orbitrap high resolution mass spectrometry (HILIC-Q-Orbitrap HRMS). The identification of metabolic features from full scan was further performed with DDA methodology on grouped quality control (QC) samples and matched with available database. Specifically, 20 amino acids and 40 derivatives were selected for targeted analysis with optimal chromatographic separation and PRM parameters. All isomers within the selected metabolites were totally separated in the robust HILIC condition. 36 of selected metabolites were well-detected and showed a good linearity and reproducibility in NIST SRM 1950 plasma. Moreover, the absolute quantification performance of targeted PRM method was systematically validated using 10 amino acids with the corresponding stable isotope-labeled internal standards (SIL-IS). Finally, the newly developed method was successfully applied to analysis of the plasma samples from patients of pancreatic benign tumor and pancreatic cancer. The significant reduction of circulating amino acids in patients with pancreatic malignancy was confirmed by targeted PRM method and other amino acids modifications as well as polar metabolites were identified with untargeted profiling. Therefore, we have established a workflow that combines specifically and reliably targeted PRM method as well as broad-coverage untargeted profiling, which provides an innovative strategy for basic and clinical metabolomics study.
    Keywords:  Amino acids and derivatives; HILIC; PRM; Q-Orbitrap HRMS; Untargeted profiling
    DOI:  https://doi.org/10.1016/j.jpba.2021.114208
  2. J Genet Genomics. 2021 Jun 01. pii: S1673-8527(21)00132-6. [Epub ahead of print]
    Ether phospholipids govern ferroptosis.
    Hyemin Lee, Li Zhuang, Boyi Gan.
      Ferroptosis is a cell death modality triggered by excessive lipid peroxidation. Two recent studies (Zou et al., 2020; Cui et al., 2021) not only reveal critical roles of ether-linked phospholipids as an additional source for providing polyunsaturated fatty acid-containing phospholipids in driving ferroptosis but also suggest a context-dependent role of TMEM189-mediated vinyl-ether phospholipid (plasmalogen) synthesis in ferroptosis.
    Keywords:  Ether phospholipids; Ferroptosis; Lipid peroxidation; Plasmalogen; TMEM189
    DOI:  https://doi.org/10.1016/j.jgg.2021.05.003
  3. Cancer Discov. 2021 Jun 25.
    Excess Polyunsaturated Fatty Acids Induce Death in Acidic Cancer Cells.
      Omega-3 polyunsaturated fatty acids (PUFA) selectively killed cancer cells in acidic conditions.
    DOI:  https://doi.org/10.1158/2159-8290.CD-RW2021-090
  4. Anal Chim Acta. 2021 Aug 15. pii: S0003-2670(21)00500-6. [Epub ahead of print]1173 338674
    Dynamic binning peak detection and assessment of various lipidomics liquid chromatography-mass spectrometry pre-processing platforms.
    Xiaodong Feng, Wenxuan Zhang, Folkert Kuipers, Ido Kema, Andrei Barcaru, Péter Horvatovich.
      Liquid chromatography-mass spectrometry (LC-MS)-based lipidomics generates large datasets that need to be interpreted using high-performance data pre-processing tools such as XCMS, mzMine, and Progenesis. These pre-processing tools rely heavily on accurate peak detection, which depends on proper setting of the peak detection mass tolerance (PDMT). The PDMT is usually set with a fixed value in either ppm or Da units. However, this fixed value may result in duplicates or missed peak detection and inaccurate peak quantification. To improve the accuracy of peak detection, we developed the dynamic binning method, which considers peak broadening described by the physics of ion separation and sets the PDMT dynamically in function of m/z. In our method, the PDMT is proportional to (mz)2 for Fourier-transform ion cyclotron resonance (FTICR), to (mz)1.5 for Orbitrap and to m/z for Quadrupole time-of-flight (Q-TOF), and is a constant for Quadrupole mass analyzer. The dynamic binning method was implemented in XCMS [1,2], and the adopted source code is available in GitHub at https://github.com/xiaodfeng/DynamicXCMS. We have compared the performance of the XCMS implemented dynamic binning with different popular lipidomics pre-processing tools to find differential compounds. We generated set samples with 43 lipid internal standards that were differentially spiked to aliquots of one human plasma lipid sample using Orbitrap LC-MS/MS. The performance of various pipelines using matched parameter sets was quantified by a quality score system that reflects the ability of a pre-processing pipeline to detect differential peaks spiked at various concentrations. The quality score indicated that our dynamic binning method improves the quantification performance of XCMS (maximum p-value 9.8·10-3 of two-sample Wilcoxon test) over its original implementation. We also showed that the XCMS with dynamic binning found differential spiked-in lipids better or with similar performance as mzMine and Progenesis do.
    Keywords:  Dynamic binning; EIC construction; LC-MS pre-Processing; Lipidomics; Peak detection
    DOI:  https://doi.org/10.1016/j.aca.2021.338674
  5. iScience. 2021 Jun 25. 24(6): 102649
    KEAP1 deficiency drives glucose dependency and sensitizes lung cancer cells and tumors to GLUT inhibition.
    Pranavi Koppula, Kellen Olszewski, Yilei Zhang, Lavanya Kondiparthi, Xiaoguang Liu, Guang Lei, Molina Das, Bingliang Fang, Masha V Poyurovsky, Boyi Gan.
      Metabolic reprogramming in cancer cells can create metabolic liabilities. KEAP1-mutant lung cancer is refractory to most current therapies. Here we show that KEAP1 deficiency promotes glucose dependency in lung cancer cells, and KEAP1-mutant/deficient lung cancer cells are more vulnerable to glucose deprivation than their WT counterparts. Mechanistically, KEAP1 inactivation in lung cancer cells induces constitutive activation of NRF2 transcription factor and aberrant expression of NRF2 target cystine transporter SLC7A11; under glucose limitation, high cystine uptake in KEAP1-inactivated lung cancer cells stimulates toxic intracellular disulfide buildup, NADPH depletion, and cell death, which can be rescued by genetic ablation of NRF2-SLC7A11 axis or treatments inhibiting disulfide accumulation. Finally, we show that KEAP1-inactivated lung cancer cells or xenograft tumors are sensitive to glucose transporter inhibitor. Together, our results reveal that KEAP1 deficiency induces glucose dependency in lung cancer cells and uncover a therapeutically relevant metabolic liability.
    Keywords:  cancer; cell biology; physiology
    DOI:  https://doi.org/10.1016/j.isci.2021.102649
  6. J Proteome Res. 2021 Jun 21.
    DIAproteomics: A Multifunctional Data Analysis Pipeline for Data-Independent Acquisition Proteomics and Peptidomics.
    Leon Bichmann, Shubham Gupta, George Rosenberger, Leon Kuchenbecker, Timo Sachsenberg, Phil Ewels, Oliver Alka, Julianus Pfeuffer, Oliver Kohlbacher, Hannes Röst.
      Data-independent acquisition (DIA) is becoming a leading analysis method in biomedical mass spectrometry. The main advantages include greater reproducibility and sensitivity and a greater dynamic range compared with data-dependent acquisition (DDA). However, the data analysis is complex and often requires expert knowledge when dealing with large-scale data sets. Here we present DIAproteomics, a multifunctional, automated, high-throughput pipeline implemented in the Nextflow workflow management system that allows one to easily process proteomics and peptidomics DIA data sets on diverse compute infrastructures. The central components are well-established tools such as the OpenSwathWorkflow for the DIA spectral library search and PyProphet for the false discovery rate assessment. In addition, it provides options to generate spectral libraries from existing DDA data and to carry out the retention time and chromatogram alignment. The output includes annotated tables and diagnostic visualizations from the statistical postprocessing and computation of fold-changes across pairwise conditions, predefined in an experimental design. DIAproteomics is well documented open-source software and is available under a permissive license to the scientific community at https://www.openms.de/diaproteomics/.
    Keywords:  automation; cloud computing; data processing; data-independent acquisition; peptidomics; proteomics; spectral library generation
    DOI:  https://doi.org/10.1021/acs.jproteome.1c00123
  7. Anal Bioanal Chem. 2021 Jun 22.
    From bedside to bench-practical considerations to avoid pre-analytical pitfalls and assess sample quality for high-resolution metabolomics and lipidomics analyses of body fluids.
    Rainer Lehmann.
      The stability of lipids and other metabolites in human body fluids ranges from very stable over several days to very unstable within minutes after sample collection. Since the high-resolution analytics of metabolomics and lipidomics approaches comprise all these compounds, the handling of body fluid samples, and thus the pre-analytical phase, is of utmost importance to obtain valid profiling data. This phase consists of two parts, sample collection in the hospital ("bedside") and sample processing in the laboratory ("bench"). For sample quality, the apparently simple steps in the hospital are much more critical than the "bench" side handling, where (bio)analytical chemists focus on highly standardized processing for high-resolution analysis under well-controlled conditions. This review discusses the most critical pre-analytical steps for sample quality from patient preparation; collection of body fluids (blood, urine, cerebrospinal fluid) to sample handling, transport, and storage in freezers; and subsequent thawing using current literature, as well as own investigations and practical experiences in the hospital. Furthermore, it provides guidance for (bio)analytical chemists to detect and prevent potential pre-analytical pitfalls at the "bedside," and how to assess the quality of already collected body fluid samples. A knowledge base is provided allowing one to decide whether or not the sample quality is acceptable for its intended use in distinct profiling approaches and to select the most suitable samples for high-resolution metabolomics and lipidomics investigations.
    Keywords:  Blood; Cerebrospinal fluid; Lipidomics; Metabolomics; Plasma; Pre-analytic; Serum; Urine
    DOI:  https://doi.org/10.1007/s00216-021-03450-0
  8. STAR Protoc. 2021 Jun 18. 2(2): 100585
    Protocol for the processing and downstream analysis of phosphoproteomic data with PhosR.
    Hani Jieun Kim, Taiyun Kim, Di Xiao, Pengyi Yang.
      Analysis of phosphoproteomic data requires advanced computational methodologies. To this end, we developed PhosR, a set of tools and methodologies implemented in R to allow the comprehensive analysis of phosphoproteomic data. PhosR enables processing steps such as imputation, normalization, and functional analysis such as kinase activity inference and signalome construction. Together, PhosR facilitates interpretation and discovery from large-scale phosphoproteomic data sets. For complete details on the use and execution of this protocol, please refer to Kim et al. (2021).
    Keywords:  Bioinformatics; Proteomics; Systems biology
    DOI:  https://doi.org/10.1016/j.xpro.2021.100585
  9. Rapid Commun Mass Spectrom. 2021 Jun 25. e9155
    Comparative LC-MS/MS lipidomic analysis of macaque heart tissue flash frozen or embedded in optimal cutting temperature polymer (OCT): Practical considerations.
    Ashish Vaswani, Armando Alcazar Magana, Eric Zimmermann, Wohaib Hasan, Jaishankar Raman, Claudia S Maier.
      RATIONALE: Biobanks of patient tissues have emerged as essential resources in biomedical research. Optimal cutting temperature (OCT) blends have shown to provide stability to the embedded tissue and is compatible with spectroscopic methods, such as infrared (IR) and Raman spectroscopy. Data derived from omics-methods are only useful if tissue damage caused by storage in OCT is minimal and well understood. In this context, we investigated the suitability of OCT storage for heart tissue destined for LC-MS/MS lipidomic studies.METHODS: To determine the compatibility of OCT storage with LC-MS/MS lipidomics studies. The lipid profiles of Macaque heart tissue snap-frozen in liquid nitrogen or stored in OCT were evaluated.
    RESULTS: We have evaluated a lipid extraction protocol suitable for OCT-embedded tissue that is compatible with LC-MS/MS. We annotated and evaluated the profiles of 306 lipid species from tissues stored in OCT or liquid nitrogen. For most of the lipid species (95.4%), the profiles were independent of the storage conditions. However, 4.6% of the lipid species; mainly plasmalogens, were affected by the storage method.
    CONCLUSION: This study shows that OCT storage is compatible with LC-MS/MS lipidomics of heart tissue, facilitating the use of biobanked tissue samples for future studies.
    DOI:  https://doi.org/10.1002/rcm.9155
  10. J Proteome Res. 2021 Jun 23.
    Omics Untargeted Key Script: R-Based Software Toolbox for Untargeted Metabolomics with Bladder Cancer Biomarkers Discovery Case Study.
    Ivan V Plyushchenko, Elizaveta S Fedorova, Natalia V Potoldykova, Konstantin A Polyakovskiy, Alexander I Glukhov, Igor A Rodin.
      Large-scale untargeted LC-MS-based metabolomic profiling is a valuable source for systems biology and biomarker discovery. Data analysis and processing are major tasks due to the high complexity of generated signals and the presence of unwanted variations. In the present study, we introduce an R-based open-source collection of scripts called OUKS (Omics Untargeted Key Script), which provides comprehensive data processing. OUKS is developed by integrating various R packages and metabolomics software tools and can be easily set up and prepared to create a custom pipeline. Novel computational features are related to quality control samples-based signal processing and are implemented by gradient boosting, tree-based, and other nonlinear regression algorithms. Bladder cancer biomarkers discovery study which is based on untargeted LC-MS profiling of urine samples is performed to demonstrate exhaustive functionality of the developed software tool. Unique examination among dozens of metabolomics-specific data curation methods was carried out at each processing step. As a result, potential biomarkers were identified, statistically validated, and described by metabolism disorders. Our study demonstrates that OUKS helps to make untargeted LC-MS metabolomic profiling with the latest computational features readily accessible in a ready-to-use unified manner to a research community.
    Keywords:  R programming; bladder cancer; data analysis; metabolomics; untargeted profiling
    DOI:  https://doi.org/10.1021/acs.jproteome.1c00392
  11. Anal Chem. 2021 Jun 22.
    Acoustic Mist Ionization Mass Spectrometry for Ultrahigh-Throughput Metabolomics Screening.
    Matthew J Smith, Delyan P Ivanov, Ralf J M Weber, Jonathan Wingfield, Mark R Viant.
      Incorporating safety data early in the drug discovery pipeline is key to reducing costly lead candidate failures. For a single drug development project, we estimate that several thousand samples per day require screening (<10 s per acquisition). While chromatography-based metabolomics has proven value at predicting toxicity from metabolic biomarker profiles, it lacks sufficiently high sample throughput. Acoustic mist ionization mass spectrometry (AMI-MS) is an atmospheric pressure ionization approach that can measure metabolites directly from 384-well plates with unparalleled speed. We sought to implement a signal processing and data analysis workflow to produce high-quality AMI-MS metabolomics data and to demonstrate its application to drug safety screening. An existing direct infusion mass spectrometry workflow was adapted, extended, optimized, and tested, utilizing three AMI-MS data sets acquired from technical and biological replicates of metabolite standards and HepG2 cell lysates and a toxicity study. Driven by criteria to minimize variance and maximize feature counts, an algorithm to extract the pulsed scan data was designed; parameters for signal-to-noise-ratio, replicate filter, sample filter, missing value filter, and RSD filter were all optimized; normalization and batch correction strategies were adapted; and cell phenotype filtering was implemented to exclude high cytotoxicity samples. The workflow was demonstrated using a highly replicated HepG2 toxicity data set, comprising 2772 samples from exposures to 16 drugs across 9 concentrations and generated in under 5 h, revealing metabolic phenotypes and individual metabolite changes that characterize specific modes of action. This AMI-MS workflow opens the door to ultrahigh-throughput metabolomics screening, increasing the rate of sample analysis by approximately 2 orders of magnitude.
    DOI:  https://doi.org/10.1021/acs.analchem.1c01616
  12. J Lipid Res. 2021 Jun 22. pii: S0022-2275(21)00076-6. [Epub ahead of print] 100094
    Lipidomic and transcriptional analysis of the Linoleoyl-omega-Hydroxyceramide biosynthetic pathway in human psoriatic lesions.
    Victoria J Tyrrell, Faraz Ali, William E Boeglin, Robert Andrews, James Burston, James C Birchall, John R Ingram, Robert C Murphy, Vincent Piguet, Alan R Brash, Valerie B O'Donnell, Christopher P Thomas.
      A complex assembly of lipids including fatty acids, cholesterol and ceramides is vital to the integrity of the mammalian epidermal barrier. The formation of this barrier requires oxidation of the substrate fatty acid, linoleate (LA), which is initiated by the enzyme 12R-lipoxygenase (LOX). In the epidermis, unoxidized LA is primarily found in long chain acylceramides termed esterified omega-hydroxy sphingosine/phytosphingosine/hydroxysphingosine (EOS/EOP/EOH, collectively EOx). The precise structure and localization of LOX-oxidised EOx in the human epidermis is unknown, as is their regulation in diseases such as psoriasis, one of the most common inflammatory diseases affecting the skin. Here, using precursor LC/MS/MS, we characterized multiple intermediates of EOx, including 9-HODE, 9,10-epoxy-13-HOME, and 9,10,13-TriHOME in healthy human epidermis likely to be formed via the epidermal LOX pathways. The top layers of the skin contained more LA, 9-HODE, and 9,10,13-TriHOME EOSs, while 9,10-epoxy-13-HOME EOS was more prevalent deeper in the stratum corneum. In psoriatic lesions, levels of native EOx and free HODEs and HOMEs were significantly elevated, while oxidized species were generally reduced. A transcriptional network analysis of human psoriatic lesions identified significantly elevated expression of the entire biosynthetic/metabolic pathway for oxygenated ceramides, suggesting a regulatory function for EOx lipids in reconstituting epidermal integrity. The role of these new lipids in progression or resolution of psoriasis is currently unknown. We also discovered the central coordinated role of the zinc finger protein transcription factor, ZIC1, in driving the phenotype of this disease. In summary, long-chain oxygenated ceramide metabolism is dysregulated at the lipidomic level in psoriasis, likely driven by the transcriptional differences also observed, and we identified ZIC1 as a potential regulatory target for future therapeutic interventions.
    Keywords:  Ceramides; EOx; ZIC1; clinical lipidology; epidermis; lipid metabolism in the skin; lipids/oxidation; lipoxygenase; mass spectrometry; sphingolipids
    DOI:  https://doi.org/10.1016/j.jlr.2021.100094
  13. Anal Chem. 2021 06 22. 93(24): 8423-8431
    A Universal and High-Throughput Proteomics Sample Preparation Platform.
    Andrew P Burns, Ya-Qin Zhang, Tuan Xu, Zhengxi Wei, Qin Yao, Yuhong Fang, Valeriu Cebotaru, Menghang Xia, Matthew D Hall, Ruili Huang, Anton Simeonov, Christopher A LeClair, Dingyin Tao.
      Major advances have been made to improve the sensitivity of mass analyzers, spectral quality, and speed of data processing enabling more comprehensive proteome discovery and quantitation. While focus has recently begun shifting toward robust proteomics sample preparation efforts, a high-throughput proteomics sample preparation is still lacking. We report the development of a highly automated universal 384-well plate sample preparation platform with high reproducibility and adaptability for extraction of proteins from cells within a culture plate. Digestion efficiency was excellent in comparison to a commercial digest peptide standard with minimal sample loss while improving sample preparation throughput by 20- to 40-fold (the entire process from plated cells to clean peptides is complete in ∼300 min). Analysis of six human cell types, including two primary cell samples, identified and quantified ∼4,000 proteins for each sample in a single high-performance liquid chromatography (HPLC)-tandem mass spectrometry injection with only 100-10K cells, thus demonstrating universality of the platform. The selected protein was further quantified using a developed HPLC-multiple reaction monitoring method for HeLa digests with two heavy labeled internal standard peptides spiked in. Excellent linearity was achieved across different cell numbers indicating a potential for target protein quantitation in clinical research.
    DOI:  https://doi.org/10.1021/acs.analchem.1c00265
  14. J Chromatogr A. 2021 Jun 09. pii: S0021-9673(21)00460-X. [Epub ahead of print]1651 462336
    A rapid, simple and sensitive microfluidic chip electrophoresis mass spectrometry method for monitoring amino acids in cell culture media.
    Meire Ribeiro da Silva, Izabela Zaborowska, Sara Carillo, Jonathan Bones.
      The development and optimization of cell culture media for biotech applications is a fundamental step of process development. The composition of cell culture media requires an ideal blend of amino acids, vitamins, nucleosides, lipids, carbohydrates, trace elements and other components. The ability to monitor these constituents is required to ensure that cells receive sufficient nutrients to facilitate growth, viability and productivity. Analysis of cell culture media is challenging due to the range and diversity of compounds contained in this matrix and normally requires time consuming methods. A rapid, simple and sensitive microfluidic chip CE-MS method is described to monitor amino acids in chemically defined cell culture media from a Chinese hamster ovary cell line cultured over a period of 10 days. The described platform enabled the separation of 16 amino acids in less than 2 minutes and without the requirement for extensive sample preparation. The analytical parameters evaluated were precision, linearity, limit of detection and limit of quantification. The majority of essential amino acids were present in cell culture growth in high concentrations compared to non-essential amino acids. Over the course of the 10 days cell culture the concentration of certain amino acids declined by up to 100%. Microfluidic chip based CE-MS methods can be used effectively to obtain the consumption rates of amino acids in cell culture media during cell growth and to perform at-line monitoring and screening of cell culture status.
    Keywords:  Amino acid analysis; Capillary electrophoresis mass spectrometry; Cell culture; Monoclonal antibody; Spent media analysis; Upstream processing
    DOI:  https://doi.org/10.1016/j.chroma.2021.462336
  15. EMBO Rep. 2021 Jun 23. e52774
    Histone acylations and chromatin dynamics: concepts, challenges, and links to metabolism.
    Sandra Nitsch, Lara Zorro Shahidian, Robert Schneider.
      In eukaryotic cells, DNA is tightly packed with the help of histone proteins into chromatin. Chromatin architecture can be modified by various post-translational modifications of histone proteins. For almost 60 years now, studies on histone lysine acetylation have unraveled the contribution of this acylation to an open chromatin state with increased DNA accessibility, permissive for gene expression. Additional complexity emerged from the discovery of other types of histone lysine acylations. The acyl group donors are products of cellular metabolism, and distinct histone acylations can link the metabolic state of a cell with chromatin architecture and contribute to cellular adaptation through changes in gene expression. Currently, various technical challenges limit our full understanding of the actual impact of most histone acylations on chromatin dynamics and of their biological relevance. In this review, we summarize the state of the art and provide an overview of approaches to overcome these challenges. We further discuss the concept of subnuclear metabolic niches that could regulate local CoA availability and thus couple cellular metabolisms with the epigenome.
    Keywords:  acylation; chromatin; histones; metabolism; microdomains
    DOI:  https://doi.org/10.15252/embr.202152774
  16. Prog Lipid Res. 2021 Jun 17. pii: S0163-7827(21)00027-8. [Epub ahead of print]83 101111
    Plasmalogens - Ubiquitous molecules occurring widely, from anaerobic bacteria to humans.
    Milada Vítová, Andrea Palyzová, Tomáš Řezanka.
      Plasmalogens are a group of lipids mainly found in the cell membranes. They occur in anaerobic bacteria and in some protozoa, invertebrates and vertebrates, including humans. Their occurrence in plants and fungi is controversial. They can protect cells from damage by reactive oxygen species, protect other phospholipids or lipoprotein particles against oxidative stress, and have been implicated as signaling molecules and modulators of membrane dynamics. Biosynthesis in anaerobic and aerobic organisms occurs by different pathways, and the main biosynthetic pathway in anaerobic bacteria was clarified only this year (2021). Many different analytical techniques have been used for plasmalogen analysis, some of which are detailed below. These can be divided into two groups: shotgun lipidomics, or electrospray ionization mass spectrometry in combination with high performance liquid chromatography (LC-MS). The advantages and limitations of both techniques are discussed here, using examples from anaerobic bacteria to specialized mammalian (human) organs.
    DOI:  https://doi.org/10.1016/j.plipres.2021.101111
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