bims-mascan 2019-10-06 papers

bims-mascan

Biomed News

on Mass spectrometry in cancer research

Issue of 2019‒10‒06
33 papers selected by
Giovanny Rodriguez Blanco
The Beatson Institute for Cancer Research

Polyunsaturated Fatty Acids from Astrocytes Activate PPAR Gamma Signaling in Cancer Cells to Promote Brain Metastasis.
Metabolic crosstalk in the breast cancer microenvironment.
Oncogenic Rag GTPase signaling enhances B cell activation and drives follicular lymphoma sensitive to pharmacological inhibition of mTOR.
Single-Cell Metabolomics by Mass Spectrometry.
Ten Major Future Challenges in Single-Cell Metabolomics.
Sample Preparation and Analysis of Single Cells Using High Performance MALDI FTICR Mass Spectrometry.
A MALDI-MS Methodology for Studying Metabolic Heterogeneity of Single Cells in a Population.
Ambient Lipidomic Analysis of Single Mammalian Oocytes and Preimplantation Embryos Using Desorption Electrospray Ionization (DESI) Mass Spectrometry.
Spatial Mapping of Cellular Metabolites Using DESI Ion Mobility Mass Spectrometry.
Identification of Metabolites in Single Cells by Ion Mobility Separation and Mass Spectrometry.
Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies.
Plasma Metabolic Signature and Abnormalities in HIV-Infected Individuals on Long-Term Successful Antiretroviral Therapy.
Laser Capture Microdissection-Liquid Vortex Capture Mass Spectrometry Metabolic Profiling of Single Onion Epidermis and Microalgae Cells.
Analysis of Lipids in Single Cells and Organelles Using Nanomanipulation-Coupled Mass Spectrometry.
Open-Source Software Tools, Databases, and Resources for Single-Cell and Single-Cell-Type Metabolomics.
Single-Probe Mass Spectrometry Analysis of Metabolites in Single Cells.
Clinical utility of emerging biomarkers in prostate cancer liquid biopsies.
Glucose Metabolism in Pancreatic Cancer.
Evaluation of Direct from Sample Metabolomics of Human Faeces using Rapid Evaporative Ionisation Mass Spectrometry (REIMS).
Dietary Sugars Alter Hepatic Fatty Acid Oxidation via Transcriptional and Post-translational Modifications of Mitochondrial Proteins.
The Effects of Doxorubicin-based Chemotherapy and Omega-3 Supplementation on Mouse Brain Lipids.
Temperature and time-dependent effects of delayed blood processing on oxylipin concentrations in human plasma.
Metabolic Diversity in Human Non-Small Cell Lung Cancer Cells.
Dysregulation of glutaminase and glutamine synthetase in cancer.
Impact of matrix effects and ionization efficiency in non-quantitative untargeted metabolomics.
Separation of 13C and 15N-Isotopologues of Amino Acids with a Primary Amine without Mass Resolution by means of O-Phthalaldehyde Derivatization and Collision Induced Dissociation.
Metabolomic analysis of Shiga toxin 2a-induced injury in conditionally immortalized glomerular endothelial cells.
Differential contribution of pyruvate carboxylation to anaplerosis and cataplerosis during non-gluconeogenic and gluconeogenic conditions in HepG2 cells.
Phosphoethanolamine Accumulation Protects Cancer Cells under Glutamine Starvation through Downregulation of PCYT2.
Recent advances in mass spectrometry (MS)-based glycoproteomics in complex biological samples.
Toward Single Cell Molecular Imaging by Matrix-Free Nanophotonic Laser Desorption Ionization Mass Spectrometry.
The effect of high glucose on lipid metabolism in the human placenta.
Applications of MicroArrays for Mass Spectrometry (MAMS) in Single-Cell Metabolomics.

Cancer Discov. 2019 Oct 02. pii: CD-19-0270. [Epub ahead of print]

Polyunsaturated Fatty Acids from Astrocytes Activate PPAR Gamma Signaling in Cancer Cells to Promote Brain Metastasis.

YongKang Zou, Andrea Watters, Nan Cheng, Caroline E Perry, Ke Xu, Gretchen M Alicea, Joshua L D Parris, Ezra Baraban, Pulak Ray, Anupma Nayak, Xiaowei Xu, Meenhard Herlyn, Maureen E Murphy, Ashani T Weeraratna, Zachary T Schug, Qing Chen.

Brain metastasis, the most ominous form of melanoma and carcinoma, is the consequence of favorable interactions between the invaded cancer cells and the brain cells. Peroxisome proliferator-activated receptor gamma (PPAR gamma has ambiguous functions in cancer development and its relevance in advanced brain metastasis remains unclear. Here, we demonstrate that astrocytes, the unique brain glia cells, activate PPAR gamma in brain metastatic cancer cells. PPAR gamma activation enhances cell proliferation and metastatic outgrowth in the brain. Mechanistically, astrocytes have a high content of polyunsaturated fatty acids that acts as 'donors' of PPAR gamma activators to the invaded cancer cells. In clinical samples, PPAR gamma signaling is significantly higher in brain metastatic lesions. Notably, systemic administration of PPAR gamma antagonist significantly reduces brain metastatic burden in vivo. Our study clarifies a pro-metastatic role for PPAR gamma signaling in cancer metastasis in the lipid rich brain microenvironment and argues for the use of PPAR gamma blockade to treat brain metastasis.

DOI: https://doi.org/10.1158/2159-8290.CD-19-0270
Eur J Cancer. 2019 Sep 30. pii: S0959-8049(19)30502-7. [Epub ahead of print]121 154-171

Metabolic crosstalk in the breast cancer microenvironment.

Ana S Dias, Catarina R Almeida, Luisa A Helguero, Iola F Duarte.

  During tumorigenesis, breast tumour cells undergo metabolic reprogramming, which generally includes enhanced glycolysis, tricarboxylic acid cycle activity, glutaminolysis and fatty acid biosynthesis. However, the extension and functional importance of these metabolic alterations may diverge not only according to breast cancer subtypes, but also depending on the interaction of cancer cells with the complex surrounding microenvironment. This microenvironment comprises a variety of non-cancerous cells, such as immune cells (e.g. macrophages, lymphocytes, natural killer cells), fibroblasts, adipocytes and endothelial cells, together with extracellular matrix components and soluble factors, which influence cancer progression and are predictive of clinical outcome. The continuous interaction between cancer and stromal cells results in metabolic competition and symbiosis, with oncogenic-driven metabolic reprogramming of cancer cells shaping the metabolism of neighbouring cells and vice versa. This review addresses current knowledge on this metabolic crosstalk within the breast tumour microenvironment (TME). Improved understanding of how metabolism in the TME modulates cancer development and evasion of tumour-suppressive mechanisms may provide clues for novel anticancer therapeutics directed to metabolic targets.

Keywords:  Breast cancer; Cell metabolism; Metabolic interplay; Tumour microenvironment

DOI:  https://doi.org/10.1016/j.ejca.2019.09.002
Nat Metab. 2019 Aug;1(8): 775-789

Oncogenic Rag GTPase signaling enhances B cell activation and drives follicular lymphoma sensitive to pharmacological inhibition of mTOR.

Ana Ortega-Molina, Nerea Deleyto-Seldas, Joaquim Carreras, Alba Sanz, Cristina Lebrero-Fernández, Camino Menéndez, Andrew Vandenberg, Beatriz Fernández-Ruiz, Leyre Marín-Arraiza, Celia de la Calle Arregui, Ana Belén Plata-Gómez, Eduardo Caleiras, Alba de Martino, Nuria Martínez-Martín, Kevin Troulé, Elena Piñeiro-Yáñez, Naoya Nakamura, Shamzah Araf, Gabriel D Victora, Jessica Okosun, Jude Fitzgibbon, Alejo Efeyan.

  The humoral immune response demands that B cells undergo a sudden anabolic shift and high cellular nutrient levels which are required to sustain the subsequent proliferative burst. Follicular lymphoma (FL) originates from B cells that have participated in the humoral response, and 15% of FL samples harbor point, activating mutations in RRAGC, an essential activator of mTORC1 downstream of the sensing of cellular nutrients. The impact of recurrent RRAGC mutations in B cell function and lymphoma is unexplored. RRAGC mutations, targeted to the endogenous locus in mice, confer a partial insensitivity to nutrient deprivation, but strongly exacerbate B cell responses and accelerate lymphomagenesis, while creating a selective vulnerability to pharmacological inhibition of mTORC1. This moderate increase in nutrient signaling synergizes with paracrine cues from the supportive T cell microenvironment that activates B cells via the PI3K-Akt-mTORC1 axis. Hence, Rragc mutations sustain induced germinal centers and murine and human FL in the presence of decreased T cell help. Our results support a model in which activating mutations in the nutrient signaling pathway foster lymphomagenesis by corrupting a nutrient-dependent control over paracrine signals from the T cell microenvironment.

Keywords:  B cell lymphoma; B lymphocytes; RRAGC; T follicular helper; apoptosis; cell growth; germinal center; mTOR; nutrient signaling; rapamycin

DOI:  https://doi.org/10.1038/s42255-019-0098-8
Methods Mol Biol. 2020 ;2064 1-8

Single-Cell Metabolomics by Mass Spectrometry.

Bindesh Shrestha.

  Single-cell level metabolomics gives a snapshot of small molecules, intermediates, and products of cellular metabolism within a biological system. These small molecules, typically less than 1 kDa in molecular weight, often provide the basis of biochemical heterogeneity within cells. The molecular differences between cells with a cell type are often attributed to random stochastic biochemical processes, cell cycle stages, environmental stress, and diseased states. In this chapter, current limitations and challenges in single-cell analysis by mass spectrometry will be discussed alongside the prospects of single-cell metabolomics in systems biology. A few selected example of the recent development in mass spectrometry tools to unravel single-cell metabolomics will be described as well.

Keywords:  Single cell; Single-cell analysis; Single-cell mass spectrometry; Single-cell metabolites; Single-cell metabolomics

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_1
Methods Mol Biol. 2020 ;2064 219-223

Ten Major Future Challenges in Single-Cell Metabolomics.

Bindesh Shrestha.

  Information on cellular metabolism at the single-cell level can unravel countless biochemical process providing invaluable biomedical insight. Single-cell analysis field is at the very early stage at this moment, and all the work done so far are proof-of-principle work by early-stage researchers. In this chapter, I have outlined ten fundamental issues that are required for the development of robust single-cell metabolomics platform using mass spectrometry (MS).

Keywords:  Single-cell analysis; Single-cell future directions; Single-cell mass spectrometry; Single-cell metabolomics; Single-cell omic

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_16
Methods Mol Biol. 2020 ;2064 125-134

Sample Preparation and Analysis of Single Cells Using High Performance MALDI FTICR Mass Spectrometry.

Bo Yang, Tina Tsui, Richard M Caprioli, Jeremy L Norris.

  Imaging mass spectrometry is a powerful technology that combines the molecular measurements of mass spectrometry with the spatial information inherent to microscopy. This unique combination of capabilities is ideally suited for the analysis of metabolites and lipids from single cells. This chapter describes a methodology for the sample preparation and analysis of single cells using high performance MALDI FTICR MS. Using this approach, we are able to generate profiles of lipid and metabolite expression from single cells that characterize cellular heterogeneity. This approach also enables the detection of variations in the expression profiles of lipids and metabolites induced by chemical stimulation of the cells. These results demonstrate that MALDI IMS provides an insightful view of lipid and metabolite expression useful in the characterization of a number of biological systems at the single cell level.

Keywords:  FTICR; Lipidomics; MALDI; Mass spectrometry; Metabolomics; Sample preparation; Single cell analysis

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_10
Methods Mol Biol. 2020 ;2064 113-124

A MALDI-MS Methodology for Studying Metabolic Heterogeneity of Single Cells in a Population.

Jasmin Krismer, Jens Sobek, Robert F Steinhoff, Rolf Brönnimann, Martin Pabst, Renato Zenobi.

  Mass spectrometry based metabolomics is the highly multiplexed, label-free analysis of small molecules such as metabolites or lipids in biological systems, and thus one of the most direct ways to characterize phenotypes. However, the phenotyping of populations with single-cell resolution is a great challenge due to the small number of molecules contained in an individual cell. Here we describe a microarray-based sample preparation workflow for MALDI mass spectrometry that has single-cell sensitivity and allows high-throughput analysis of lipids and pigments in single algae cells. The microarray targets receive individual cells in 1430 separate spots that allow the cells to be lysed individually without cross-contamination. Using positive ion mode and 2,5-dihydroxybenzoic acid as the MALDI matrix, the mass spectra unveil information about the relative composition of more than 20 different lipids/pigments in each individual cell within the population. Thus, the method allows the analysis of cellular phenotypes in a population on a completely new level.

Keywords:  Chlamydomonas reinhardtii; High-throughput analysis; Lipid profiling; MALDI-mass spectrometry; Single-cell analysis

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_9
Methods Mol Biol. 2020 ;2064 159-179

Ambient Lipidomic Analysis of Single Mammalian Oocytes and Preimplantation Embryos Using Desorption Electrospray Ionization (DESI) Mass Spectrometry.

Christina R Ferreira, Valentina Pirro, Alan K Jarmusch, Clint M Alfaro, R Graham Cooks.

  Desorption electrospray ionization (DESI) is a spray-based ambient ionization method for mass spectrometry (MS) that generates ions in native atmospheric conditions (e.g., pressure and temperature). Ambient ionization allows in situ analysis of unmodified samples by eliminating analyte extraction and separation steps before MS. Lipid analysis of individual mammalian oocytes and preimplantation embryos is challenging because of their complex chemical composition and minute dimensions (100-300 μm in diameter). Nonetheless, DESI-MS can provide comprehensive lipidomic profiles of individual oocytes or embryos using a fast and simple workflow. DESI-MS lipid profiles include many classes of lipids such as phosphatidylcholines (PC), triacylglycerols (TAG), free fatty acids (FFA), phosphatidylethanolamines (PE), phosphatidylinositols (PI), phosphatidylserines (PS), diacylglycerols (DAG), ubiquinone, cholesterol and cholesterol derivatives (e.g., cholesterol sulfate and cholesterol esters). Depending on the mass spectrometer used, there is the additional possibility of obtaining structural information of lipids via MSn, and molecular formulae via high resolution MS. Here, we describe the procedures for sample handling, the DESI-MS experimental arrangement, and the data collection and data analysis using low and high-resolution mass spectrometers (such as a linear ion trap and Orbitrap mass analyzer, respectively), as well as strategies for structural characterization of lipids. Lastly, we detail our workflow for relating the chemical information obtained by DESI-MS into the biological context of oocyte and embryo metabolism.

Keywords:  Ambient mass spectrometry; DESI-MS; Exact mass measurement; Lipids; Multidimensional MS scan; Multivariate statistics; Reactive DESI; Single cell

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_13
Methods Mol Biol. 2020 ;2064 181-190

Spatial Mapping of Cellular Metabolites Using DESI Ion Mobility Mass Spectrometry.

Anthony Midey, Hernando Olivos, Bindesh Shrestha.

  Spatial mapping of cellular metabolites, such as neurotransmitters and lipids, on the tissue, can increase our understanding of the biological functions of those molecules. Mass spectrometry imaging (MSI) techniques, such as desorption electrospray ionization (DESI), have not demonstrated the ability to perform metabolite analysis at mammalian single cell level yet. However, they can be a valuable tool to provide insight into cellular metabolism in a very small population (tens) of cells. DESI MSI, coupled with ion mobility separation, improves the peak capacity and signal-to-noise ratio of detected analytes by separating a molecule of interest from interfering isobaric species found in a complex biological matrix. Here we present a protocol for mapping cellular metabolites neurotransmitters, such as serotonin, adenosine, and glutamine directly in brain tissue samples using DESI MSI.

Keywords:  Collision cross section; DESI; Ion mobility; Metabolite imaging; Traveling-wave ion mobility

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_14
Methods Mol Biol. 2020 ;2064 9-18

Identification of Metabolites in Single Cells by Ion Mobility Separation and Mass Spectrometry.

Linwen Zhang, Linda L Allworth, Akos Vertes.

  Non-targeted metabolic analysis of single cells by mass spectrometry (MS) is important for understanding individual cell functions and characterizing cell-to-cell heterogeneity. However, identifying biomolecules in single cells presents significant challenges due to the low picoliter volume samples and the structural diversity of metabolites. Capillary microsampling electrospray ionization (ESI) MS with ion mobility separation (IMS) enables the analysis of single cells under ambient conditions with minimum sample pretreatment and improved specificity. Here, we describe a protocol for the analysis of the metabolic makeup, and the identification of ions produced from single cells by capillary microsampling ESI-IMS-MS.

Keywords:  Collision cross-section; Ion mobility separation; Isobaric ions; Mass spectrometry; Metabolomics; Single-cell analysis

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_2
EMBO Mol Med. 2019 Sep 30. e10427

Plasma Proteome Profiling to detect and avoid sample-related biases in biomarker studies.

Philipp E Geyer, Eugenia Voytik, Peter V Treit, Sophia Doll, Alisa Kleinhempel, Lili Niu, Johannes B Müller, Marie-Luise Buchholtz, Jakob M Bader, Daniel Teupser, Lesca M Holdt, Matthias Mann.

  Plasma and serum are rich sources of information regarding an individual's health state, and protein tests inform medical decision making. Despite major investments, few new biomarkers have reached the clinic. Mass spectrometry (MS)-based proteomics now allows highly specific and quantitative readout of the plasma proteome. Here, we employ Plasma Proteome Profiling to define quality marker panels to assess plasma samples and the likelihood that suggested biomarkers are instead artifacts related to sample handling and processing. We acquire deep reference proteomes of erythrocytes, platelets, plasma, and whole blood of 20 individuals (> 6,000 proteins), and compare serum and plasma proteomes. Based on spike-in experiments, we determine sample quality-associated proteins, many of which have been reported as biomarker candidates as revealed by a comprehensive literature survey. We provide sample preparation guidelines and an online resource ( www.plasmaproteomeprofiling.org) to assess overall sample-related bias in clinical studies and to prevent costly miss-assignment of biomarker candidates.

Keywords:  biomarker discovery; mass spectrometry; plasma proteomics; sample quality; study design

DOI:  https://doi.org/10.15252/emmm.201910427
Metabolites. 2019 Sep 30. pii: E210. [Epub ahead of print]9(10):

Plasma Metabolic Signature and Abnormalities in HIV-Infected Individuals on Long-Term Successful Antiretroviral Therapy.

Hemalatha Babu, Maike Sperk, Anoop T Ambikan, Gladys Rachel, Vinod Kumar Viswanathan, Srikanth P Tripathy, Piotr Nowak, Luke Elizabeth Hanna, Ujjwal Neogi.

  Targeted metabolomics studies reported metabolic abnormalities in both treated and untreated people living with human immunodeficiency virus (HIV) (PLHIV). The present study aimed to understand the plasma metabolomic changes and predicted the risk of accelerated aging in PLHIV on long-term suppressive antiretroviral therapy (ART) in a case-control study setting and its association with the plasma proteomics biomarkers of inflammation and neurological defects. Plasma samples were obtained from PLHIV on successful long-term ART for more than five years (n = 22) and matched HIV-negative healthy individuals (n = 22, HC herein). Untargeted metabolite profiling was carried out using ultra-high-performance liquid chromatography/mass spectrometry/mass spectrometry (UHPLC/MS/MS). Plasma proteomics profiling was performed using proximity extension assay targeting 184 plasma proteins. A total of 250 metabolites differed significantly (p < 0.05, q < 0.1) between PLHIV and HC. Plasma levels of several essential amino acids except for histidine, branched-chain amino acids, and aromatic amino acids (phenylalanine, tyrosine, tryptophan) were significantly lower in PLHIV compared to HC. Machine-learning prediction of metabolite changes indicated a higher risk of inflammatory and neurological diseases in PLHIV. Metabolic abnormalities were observed in amino-acid levels, energetics, and phospholipids and complex lipids, which may reflect known differences in lipoprotein levels in PLHIV that can resemble metabolic syndrome (MetS).

Keywords:  HIV/acquired immune deficiency syndrome (AIDS); antiretroviral therapy; targeted proteomics; untargeted metabolomics

DOI:  https://doi.org/10.3390/metabo9100210
Methods Mol Biol. 2020 ;2064 89-101

Laser Capture Microdissection-Liquid Vortex Capture Mass Spectrometry Metabolic Profiling of Single Onion Epidermis and Microalgae Cells.

John F Cahill, Vilmos Kertesz.

  Laser capture microdissection is a valuable technique in individually isolating single cells whether in tissue networks or deposited from a cell suspension. New developments have enabled coupling of laser capture microdissection with mass spectrometry via liquid vortex capture sampling probe. This enables online metabolic profiling of sectioned cells. Here, we describe the protocol used to deposit, isolate, and individually chemically characterize single Allium cepa and Chlamydomonas reinhardtii cells by laser capture microdissection-liquid vortex capture mass spectrometry.

Keywords:  Laser capture microdissection; Liquid-vortex capture; Mass spectrometry; Metabolites; Microalgae; Onion epidermis cell; Single cell

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_7
Methods Mol Biol. 2020 ;2064 19-30

Analysis of Lipids in Single Cells and Organelles Using Nanomanipulation-Coupled Mass Spectrometry.

Mandy S Phelps, Guido F Verbeck.

  The ability to discriminately analyze the chemical constituents of single cells and organelles is highly sought after and necessary to establish true biomarkers. Some major challenges of individual cell analysis include requirement and expenditure of a large sample of cells as well as extensive extraction and separation techniques. Here, we describe methods to perform individual cell and organelle extractions of both tissues and cells in vitro using nanomanipulation coupled to mass spectrometry. Lipid profiles display heterogeneity from extracted adipocytes and lipid droplets, demonstrating the necessity for single cell analysis. The application of these techniques can be applied to other cell and organelle types for selective and thorough monitoring of disease progression and biomarker discovery.

Keywords:  DOMS; Lipidomics; MALDI; Mass spectrometry; Nanoelectrospray; Nanomanipulation; Single cell

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_3
Methods Mol Biol. 2020 ;2064 191-217

Open-Source Software Tools, Databases, and Resources for Single-Cell and Single-Cell-Type Metabolomics.

Biswapriya B Misra.

  In this age of -omics data-guided big data revolution, metabolomics has received significant attention as compared to genomics, transcriptomics, and proteomics for its proximity to the phenotype, the promises it makes and the challenges it throws. Although metabolomes of entire organisms, organs, biofluids, and tissues are of immense interest, a cell-specific resolution is deemed critical for biomedical applications where a granular understanding of cellular metabolism at cell-type and subcellular resolution is desirable. Mass spectrometry (MS) is a versatile technique that is used to analyze a broad range of compounds from different species and cell-types, with high accuracy, resolution, sensitivity, selectivity, and fast data acquisition speeds. With recent advances in MS and spectroscopy-based platforms, the research community is able to generate high-throughput data sets from single cells. However, it is challenging to handle, store, process, analyze, and interpret data in a routine manner. In this treatise, I present a workflow of metabolomics data generation from single cells and single-cell types to their analysis, visualization, and interpretation for obtaining biological insights.

Keywords:  Analysis; Animal; Cell; Computational; Data; Database; Mass spectrometry; Metabolomics; Microbial; Network; Pathway; Plant; Single cell; Single-cell type; Software; Statistical; Tool; Web server; –Omics

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_15
Methods Mol Biol. 2020 ;2064 61-71

Single-Probe Mass Spectrometry Analysis of Metabolites in Single Cells.

Ning Pan, Wei Rao, Zhibo Yang.

  Mass spectrometry (MS) is an indispensable analytical technique for bioanalysis. Based on the measurement of mass/charge ratios (m/z) of ions, MS can be used for sensitive detection and accurate identification of species of interest. In traditional studies, MS is utilized to measure analytes in prepared solutions or gas-phase samples. Benefited from recent development of sampling and ionization approaches, MS has been extensively applied to the analysis of broad ranges of biological samples. We have developed a new device, the Single-probe, that can be used for in situ, real-time MS analysis of metabolites inside individual living cells. The Single-probe is a miniaturized multifunctional sampling and ionization device that is directly coupled to the mass spectrometer. With a sampling tip size smaller than 10 μm, we can insert the Single-probe tip into single cells to extract intracellular compounds, which are analyzed using MS in real-time. We have successfully used the Single-probe MS technique to detect a variety of endogenous and exogenous cellular metabolites in individual eukaryotic cells. Single cell mass spectrometry (SCMS) is a new scientific technology that has the potential to reshape approaches in biological and pharmaceutical bioanalytical research.

Keywords:  Mass spectrometry; Metabolites; Single cell; Single-probe

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_5
Expert Rev Mol Diagn. 2019 Oct 02.

Clinical utility of emerging biomarkers in prostate cancer liquid biopsies.

Emmy Boerrigter, Levi N Groen, Nielka P van Erp, Gerald W Verhaegh, Jack A Schalken.

  Introduction Prostate cancer (PCa) is one of the most common malignancies in men and a major cause of cancer deaths among men worldwide. Prostate specific antigen (PSA) monitoring and histopathological examination of tumor biopsies remain gold standards in PCa diagnostics. These clinical parameters are not well suited for patient stratification, predicting and monitoring treatment response. On the other hand, liquid biopsies offer a unique opportunity to easily isolate tumor-derived material for longitudinal clinical assessment. Areas covered In this review we focus on the clinical application of novel liquid biomarkers that have the potential to monitor and stratify patients in order to achieve better therapeutic effects and improve clinical outcomes. Enumeration and characterization of circulating tumor cells (CTCs), tumor-educated platelets, exosomes, and cell-free nucleic acids have been studied for their clinical utility in PCa diagnostics, prognostics, monitoring treatment response and guiding treatment choice. Expert opinion Liquid biomarkers have high potential to be used for prognosis, monitoring treatment response and guiding treatment selection. Although there is a remarkable progress in PCa biomarker discovery, their clinical validation is very limited. Research should be focused on biomarker validation and the incorporation of these biomarkers in clinical practice.

Keywords:  androgens; biomarkers; cell-free tumor DNA; circulating tumor cell; exosomes; liquid biopsy; long non-coding RNA; microRNA; prostate cancer; therapy response

DOI:  https://doi.org/10.1080/14737159.2019.1675515
Cancers (Basel). 2019 Sep 29. pii: E1460. [Epub ahead of print]11(10):

Glucose Metabolism in Pancreatic Cancer.

Liang Yan, Priyank Raj, Wantong Yao, Haoqiang Ying.

  Pancreatic ductal adenocarcinoma (PDAC) is one of the most aggressive and lethal cancers, with a five-year survival rate of around 5% to 8%. To date, very few available drugs have been successfully used to treat PDAC due to the poor understanding of the tumor-specific features. One of the hallmarks of pancreatic cancer cells is the deregulated cellular energetics characterized by the "Warburg effect". It has been known for decades that cancer cells have a dramatically increased glycolytic flux even in the presence of oxygen and normal mitochondrial function. Glycolytic flux is the central carbon metabolism process in all cells, which not only produces adenosine triphosphate (ATP) but also provides biomass for anabolic processes that support cell proliferation. Expression levels of glucose transporters and rate-limiting enzymes regulate the rate of glycolytic flux. Intermediates that branch out from glycolysis are responsible for redox homeostasis, glycosylation, and biosynthesis. Beyond enhanced glycolytic flux, pancreatic cancer cells activate nutrient salvage pathways, which includes autophagy and micropinocytosis, from which the generated sugars, amino acids, and fatty acids are used to buffer the stresses induced by nutrient deprivation. Further, PDAC is characterized by extensive metabolic crosstalk between tumor cells and cells in the tumor microenvironment (TME). In this review, we will give an overview on recent progresses made in understanding glucose metabolism-related deregulations in PDAC.

Keywords:  glucose metabolism; pancreatic cancer

DOI:  https://doi.org/10.3390/cancers11101460
Anal Chem. 2019 Oct 04.

Evaluation of Direct from Sample Metabolomics of Human Faeces using Rapid Evaporative Ionisation Mass Spectrometry (REIMS).

Simon J S Cameron, James Alexanders, Frances Bolt, Adam Burke, Hutan Ashrafian, Julian P Teare, Julian R Marchesi, James M Kinross, Jia V Li, Zoltan Takats.

Mass spectrometry is a powerful tool in the investigation of the human faecal metabolome. However, current approaches require time-consuming sample preparation, chromatographic separations, and consequently long analytical run times. Rapid evaporative ionisation mass spectrometry (REIMS) is a method of ambient ionisation mass spectrometry and has been utilised in the metabolic profiling of a diverse range of biological materials, including human tissue, cell culture lines, and microorganisms. Here, we describe the use of an automated, high-throughput REIMS robotic platform for direct analysis of human faeces. Through the analysis of faecal samples from five healthy male participants, REIMS analytical parameters were optimised and used to assess the chemical information obtainable using REIMS. Within the faecal samples analysed, bile acids, including primary, secondary, and conjugate species were identified, and phospholipids of possible bacterial origin were detected. In addition, the effect of storage conditions and consecutive freeze/thaw cycles was determined. Within the REIMS mass spectra, the lower molecular weight metabolites, such as fatty acids, were shown to be significantly affected by storage conditions for prolonged periods at temperatures above -80°C, and consecutive freeze/thaw cycles. However, the complex lipid region was shown to be unaffected by these conditions. A further cohort of 50 faecal samples, collected from patients undergoing bariatric surgery, were analysed using the optimised REIMS parameters, and the complex lipid region mass spectra used for multivariate modelling. This analysis showed a predicted separation between pre- and post-surgery specimens, suggesting that REIMS analysis can detect biological differences, such as microbiome-level differences, which have traditionally been reliant upon methods utilising extensive sample preparations and chromatographic separations and/or DNA sequencing.

DOI: https://doi.org/10.1021/acs.analchem.9b02358
Cell Metab. 2019 Oct 01. pii: S1550-4131(19)30504-2. [Epub ahead of print]30(4): 735-753.e4

Dietary Sugars Alter Hepatic Fatty Acid Oxidation via Transcriptional and Post-translational Modifications of Mitochondrial Proteins.

Samir Softic, Jesse G Meyer, Guo-Xiao Wang, Manoj K Gupta, Thiago M Batista, Hans P M M Lauritzen, Shiho Fujisaka, Dolors Serra, Laura Herrero, Jennifer Willoughby, Kevin Fitzgerald, Olga Ilkayeva, Christopher B Newgard, Bradford W Gibson, Birgit Schilling, David E Cohen, C Ronald Kahn.

  Dietary sugars, fructose and glucose, promote hepatic de novo lipogenesis and modify the effects of a high-fat diet (HFD) on the development of insulin resistance. Here, we show that fructose and glucose supplementation of an HFD exert divergent effects on hepatic mitochondrial function and fatty acid oxidation. This is mediated via three different nodes of regulation, including differential effects on malonyl-CoA levels, effects on mitochondrial size/protein abundance, and acetylation of mitochondrial proteins. HFD- and HFD plus fructose-fed mice have decreased CTP1a activity, the rate-limiting enzyme of fatty acid oxidation, whereas knockdown of fructose metabolism increases CPT1a and its acylcarnitine products. Furthermore, fructose-supplemented HFD leads to increased acetylation of ACADL and CPT1a, which is associated with decreased fat metabolism. In summary, dietary fructose, but not glucose, supplementation of HFD impairs mitochondrial size, function, and protein acetylation, resulting in decreased fatty acid oxidation and development of metabolic dysregulation.

Keywords:  acetylation; fatty acid oxidation; fatty liver disease; fructose; glucose; ketohexokinase; mass spectrometry; mitochondria; obesity; sugar

DOI:  https://doi.org/10.1016/j.cmet.2019.09.003
Metabolites. 2019 Sep 29. pii: E208. [Epub ahead of print]9(10):

The Effects of Doxorubicin-based Chemotherapy and Omega-3 Supplementation on Mouse Brain Lipids.

Djawed Bennouna, Melissa Solano, Tonya S Orchard, A Courtney DeVries, Maryam Lustberg, Rachel E Kopec.

  Chemotherapy-induced cognitive impairment affects ~30% of breast cancer survivors, but the effects on how chemotherapy impacts brain lipids, and how omega-3 polyunsaturated fatty acid supplementation may confer protection, is unknown. Ovariectomized mice were randomized to two rounds of injections of doxorubicin + cyclophosphamide or vehicle after consuming a diet supplemented with 2% or 0% EPA+DHA, and sacrificed 4, 7, and 14 days after the last injection (study 1, n = 120) or sacrificed 10 days after the last injection (study 2, n = 40). Study 1 whole brain samples were extracted and analyzed by UHPLC-MS/MS to quantify specialized pro-resolving mediators (SPMs). Lipidomics analyses were performed on hippocampal extracts from study 2 to determine changes in the brain lipidome. Study 1 results: only resolvin D1 was present in all samples, but no differences in concentration were observed (P > 0.05). Study 2 results: chemotherapy was positively correlated with omega-9 fatty acids, and EPA+DHA supplementation helped to maintain levels of plasmalogens. No statistically significant chemotherapy*diet effect was observed. Results demonstrate a limited role of SPMs in the brain post-chemotherapy, but a significant alteration of hippocampal lipids previously associated with other models of cognitive impairment (i.e., Alzheimer's and Parkinson's disease).

Keywords:  DHA; EPA; chromatography; hippocampus; lipidomics; mass spectrometry; specialized pro-resolving mediators

DOI:  https://doi.org/10.3390/metabo9100208
Prostaglandins Leukot Essent Fatty Acids. 2019 Sep 05. pii: S0952-3278(19)30125-5. [Epub ahead of print]150 31-37

Temperature and time-dependent effects of delayed blood processing on oxylipin concentrations in human plasma.

Christopher E Ramsden, Zhi-Xin Yuan, Mark S Horowitz, Daisy Zamora, Sharon F Majchrzak-Hong, Beverly S Muhlhausler, Ameer Y Taha, Maria Makrides, Robert A Gibson.

  BACKGROUND: Oxidized derivatives of polyunsaturated fatty acids, collectively known as oxylipins, are labile bioactive mediators with diverse roles in human physiology and pathology. Oxylipins are increasingly being measured in plasma collected in clinical studies to investigate biological mechanisms and as pharmacodynamic biomarkers for nutrient-based and drug-based interventions. Whole blood is generally stored either on ice or at room temperature prior to processing. However, the potential impacts of delays in processing, and of temperature prior to processing, on oxylipin concentrations are incompletely understood.OBJECTIVE: To evaluate the effects of delayed processing of blood samples in a timeframe that is typical of a clinical laboratory setting, using typical storage temperatures, on concentrations of representative unesterified oxylipins measured by liquid chromatography-tandem mass spectrometry.
DESIGN: Whole blood (drawn on three separate occasions from a single person) was collected into 5 mL purple-top potassium-EDTA tubes and stored for 0, 10, 20, 30, 60 or 120 min at room temperature or on wet ice, followed by centrifugation at 4 °C for 10 min with plasma collection. Each sample was run in duplicate, therefore there were six tubes and up to six data points at each time point for each oxylipin at each condition (ice/room temperature). Representative oxylipins derived from arachidonic acid, docosahexaenoic acid, and linoleic acid were quantified by liquid chromatography tandem mass spectrometry. Longitudinal models were used to estimate differences between temperature groups 2 h after blood draw.
RESULTS: We found that most oxylipins measured in human plasma in traditional potassium-EDTA tubes are reasonably stable when stored on ice for up to 2 h prior to processing, with little evidence of auto-oxidation in either condition. By contrast, in whole blood stored at room temperature, substantial time-dependent increases in the 12-lipoxygenase-derived (12-HETE, 14-HDHA) and platelet-derived (thromboxane B2) oxylipins were observed.
CONCLUSION: These findings suggest that certain plasma oxylipins can be measured with reasonable accuracy despite delayed processing for up to 2 h when blood is stored on ice prior to centrifugation. 12-Lipoxygenase- and platelet-derived oxylipins may be particularly sensitive to post-collection artifact with delayed processing at room temperature. Future studies are needed to determine impacts of duration and temperature of centrifugation on oxylipin concentrations.

Keywords:  Blood processing; Oxylipins; Peroxidation; Plasma; Stability

DOI:  https://doi.org/10.1016/j.plefa.2019.09.001
Mol Cell. 2019 Sep 24. pii: S1097-2765(19)30683-5. [Epub ahead of print]

Metabolic Diversity in Human Non-Small Cell Lung Cancer Cells.

Pei-Hsuan Chen, Ling Cai, Kenneth Huffman, Chendong Yang, Jiyeon Kim, Brandon Faubert, Lindsey Boroughs, Bookyung Ko, Jessica Sudderth, Elizabeth A McMillan, Luc Girard, Dong Chen, Michael Peyton, Misty D Shields, Bo Yao, David S Shames, Hyun Seok Kim, Brenda Timmons, Ikuo Sekine, Rebecca Britt, Stephanie Weber, Lauren A Byers, John V Heymach, Jing Chen, Michael A White, John D Minna, Guanghua Xiao, Ralph J DeBerardinis.

  Intermediary metabolism in cancer cells is regulated by diverse cell-autonomous processes, including signal transduction and gene expression patterns, arising from specific oncogenotypes and cell lineages. Although it is well established that metabolic reprogramming is a hallmark of cancer, we lack a full view of the diversity of metabolic programs in cancer cells and an unbiased assessment of the associations between metabolic pathway preferences and other cell-autonomous processes. Here, we quantified metabolic features, mostly from the 13C enrichment of molecules from central carbon metabolism, in over 80 non-small cell lung cancer (NSCLC) cell lines cultured under identical conditions. Because these cell lines were extensively annotated for oncogenotype, gene expression, protein expression, and therapeutic sensitivity, the resulting database enables the user to uncover new relationships between metabolism and these orthogonal processes.

Keywords:  (13)C stable isotope labeling; cancer metabolism; cell lines; gene expression; glucose; glutamine; non-small cell lung cancer; oncogenotypes; protein expression; therapeutic sensitivity

DOI:  https://doi.org/10.1016/j.molcel.2019.08.028
Cancer Lett. 2019 Sep 28. pii: S0304-3835(19)30483-5. [Epub ahead of print]

Dysregulation of glutaminase and glutamine synthetase in cancer.

José M Matés, José A Campos-Sandoval, Juan de Los Santos-Jiménez, Javier Márquez.

  Besides fast glucose catabolism, many types of cancers are characterized by elevated glutamine consumption. Medical oncology pursuits to block specific pathways, mainly glycolysis and glutaminolysis, in tumor cells to arrest cancer development. This strategy frequently induces adaptive metabolic resistance that must be countered. Combination therapy is an anticancer synergistic tool to overcome both cancer growth and resistance mechanisms. Dysregulation of glutaminase and glutamine synthetase are key events that allow anabolic adaptation of tumors. Several specific drugs that inhibit metabolic enzymes dealing with glutamine metabolism have been able to eliminate some neoplasms. Targeting the tumor microenvironment can be also another essential factor to be taken into account when single or combined cancer metabolic therapy fails.

Keywords:  Cancer metabolism; Combination therapy; Glutaminase isoenzymes; Glutamine; Glutamine synthetase; Synergistic inhibitors

DOI:  https://doi.org/10.1016/j.canlet.2019.09.011
Metabolomics. 2019 Oct 04. 15(10): 135

Impact of matrix effects and ionization efficiency in non-quantitative untargeted metabolomics.

Casey A Chamberlain, Vanessa Y Rubio, Timothy J Garrett.

  INTRODUCTION: LC-MS-based untargeted metabolomics has become increasingly popular due to the vast amount of information gained in a single analysis. Many studies utilize metabolomics to profile metabolic changes in various representative biofluids, tissues, or other sample types. Most analyses are performed measuring changes in the metabolic pool of a single biological matrix due to an altered phenotype, such as disease versus normal. Measurements in such experiments are typically highly reproducible with little variation due to analytical and technological advancements in mass spectrometry. With the expanded application of metabolomics into various non-analytical scientific disciplines, the emergence of studies comparing the signal intensities of specific analytes across different biological matrices (e.g. plasma vs. urine) is becoming more common, but the matrix effect between sample types is often neglected. Additionally, the practice of comparing the signal intensities of different analytes and correlating to relative abundance is also increasingly prevalent, but the response ratio between analytes due to differences in ionization efficiency is not always accounted for in data analysis. This report serves to communicate and raise awareness of these two well-recognized issues to prevent improper data interpretation in the field of metabolomics.OBJECTIVES: We demonstrate the impact of matrix effects and ionization efficiency with labeled analytical standards in human plasma, serum, and urine and describe how the direct comparison of non-quantitative signal intensities between biofluids, as well as between different analytes in the same biofluid, in untargeted metabolomics is inaccurate without proper response corrections.
METHODS: Human plasma, serum, and urine (n = 4 technical replicates per biofluid) were spiked with a panel of labeled internal standards all at identical concentrations, simultaneously extracted, and analyzed by UHPLC-HRMS. Signal intensities were compared for demonstration of the impact of matrix effects in untargeted metabolomics. A neat mixture of two co-eluting, structurally-similar labeled standards at the same concentration was also analyzed to demonstrate the effect of ionization efficiency on signal intensity.
RESULTS: Despite being spiked at identical concentrations, labeled standards we examined in this study showed significant differences in their signal intensities between biofluids, as well as from each other in the same biofluid, due to matrix effects. Co-eluting standards were also found to yield significantly different signal intensities at identical concentrations due to differences in ionization efficiency.
CONCLUSIONS: Due to the presence of matrix effects in untargeted, non-quantitative metabolomics, the signal intensity of any single analyte cannot be directly compared to the signal intensity of that same analyte (or any other analyte) between any two different matrices. Due to differences in ionization efficiency, the signal intensity of any single analyte cannot be directly compared to the signal intensity of any other analyte, even in the same matrix.

Keywords:  Ionization efficiency; LC–MS; Mass spectrometry; Matrix effect; Metabolomics

DOI:  https://doi.org/10.1007/s11306-019-1597-z
Anal Chem. 2019 Oct 02.

Separation of 13C and 15N-Isotopologues of Amino Acids with a Primary Amine without Mass Resolution by means of O-Phthalaldehyde Derivatization and Collision Induced Dissociation.

Jannick Kappelmann, Martin Bey Szlig, Katharina Nöh, Stephan Noack.

Computational and experimental advances of recent years have culminated in establishing 13C-Metabolic Flux Analysis (13C-MFA) as a routine methodology to unravel the fluxome. As the acronym suggests, 13C-MFA has relied on the relative abundance of 13C-isotopes in metabolites for flux inference, most commonly measured by mass spectrometry. In this manuscript we expand the scope of labeling measurements to the case of simultaneous 13C and 15N labeling of amino acids. Analytically, the separation of isotopologues of this metabolite class can only be achieved at resolving power beyond 65,000. In this manuscript we harvest an overlooked property of the collision induced dissociation of amino acid adducts to discern 13C- and 15N- isotopologues of amino acids with a primary amine without separating them in the m/z domain.

DOI: https://doi.org/10.1021/acs.analchem.9b01788
Metabolomics. 2019 Oct 01. 15(10): 131

Metabolomic analysis of Shiga toxin 2a-induced injury in conditionally immortalized glomerular endothelial cells.

Christian Patry, Kathrin Plotnicki, Christian Betzen, Alba Perez Ortiz, Kirk L Pappan, Simon C Satchell, Peter W Mathieson, Martina Bielaszewska, Helge Karch, Burkhard Tönshoff, Neysan Rafat.

  INTRODUCTION: Shiga toxin 2a (Stx2a) induces hemolytic uremic syndrome (STEC HUS) by targeting glomerular endothelial cells (GEC).OBJECTIVES: We investigated in a metabolomic analysis the response of a conditionally immortalized, stable glomerular endothelial cell line (ciGEnC) to Stx2a stimulation as a cell culture model for STEC HUS.
METHODS: CiGEnC were treated with tumor necrosis factor-(TNF)α, Stx2a or sequentially with TNFα and Stx2a. We performed a metabolomic high-throughput screening by lipid- or gas chromatography and subsequent mass spectrometry. Metabolite fold changes in stimulated ciGEnC compared to untreated cells were calculated.
RESULTS: 320 metabolites were identified and investigated. In response to TNFα + Stx2a, there was a predominant increase in intracellular free fatty acids and amino acids. Furthermore, lipid- and protein derived pro-inflammatory mediators, oxidative stress and an augmented intracellular energy turnover were increased in ciGEnC. Levels of most biochemicals related to carbohydrate metabolism remained unchanged.
CONCLUSION: Stimulation of ciGEnC with TNFα + Stx2a is associated with profound metabolic changes indicative of increased inflammation, oxidative stress and energy turnover.

Keywords:  Conditionally immortalized glomerular endothelial cells; Hemolytic uremic syndrome; Metabolomics; Shiga toxin

DOI:  https://doi.org/10.1007/s11306-019-1594-2
Arch Biochem Biophys. 2019 Oct 01. pii: S0003-9861(19)30468-0. [Epub ahead of print] 108124

Differential contribution of pyruvate carboxylation to anaplerosis and cataplerosis during non-gluconeogenic and gluconeogenic conditions in HepG2 cells.

Siriluck Wattanavanitchakorn, Israr-Ul H Ansari, Mahmoud El Azzouny, Melissa J Longacre, Scott W Stoker, Sarawut Jitrapakdee, Michael J MacDonald.

  Pyruvate carboxylase (PC) is an anaplerotic enzyme that supplies oxaloacetate to mitochondria enabling the maintenance of other metabolic intermediates consumed by cataplerosis. Using liquid chromatography mass spectrometry (LC-MS) to measure metabolic intermediates derived from uniformly labeled 13C6-glucose or [3-13C]l-lactate, we investigated the contribution of PC to anaplerosis and cataplerosis in the liver cell line HepG2. Suppression of PC expression by short hairpin RNA lowered incorporation of 13C glucose incorporation into tricarboxylic acid cycle intermediates, aspartate, glutamate and sugar derivatives, indicating impaired cataplerosis. The perturbation of these biosynthetic pathways is accompanied by a marked decrease of cell viability and proliferation. In contrast, under gluconeogenic conditions where the HepG2 cells use lactate as a carbon source, pyruvate carboxylation contributed very little to the maintenance of these metabolites. Suppression of PC did not affect the percent incorporation of 13C-labeled carbon from lactate into citrate, α-ketoglutarate, malate, succinate as well as aspartate and glutamate, suggesting that under gluconeogenic condition, PC does not support cataplerosis from lactate.

Keywords:  Anaplerosis; Cataplerosis; Gluconeogenesis; Metabolic flux; PC; PEPCK; Phosphoenolpyruvate carboxykinase; Pyruvate carboxylase; TCA; TCA cycle; Tricarboxylic acid cycle

DOI:  https://doi.org/10.1016/j.abb.2019.108124
Cell Rep. 2019 Oct 01. pii: S2211-1247(19)31149-0. [Epub ahead of print]29(1): 89-103.e7

Phosphoethanolamine Accumulation Protects Cancer Cells under Glutamine Starvation through Downregulation of PCYT2.

Tsuyoshi Osawa, Teppei Shimamura, Kyoko Saito, Yoko Hasegawa, Naoko Ishii, Miyuki Nishida, Ritsuko Ando, Ayano Kondo, Muyassar Anwar, Rika Tsuchida, Shinjiro Hino, Akihisa Sakamoto, Kaori Igarashi, Kaori Saitoh, Keiko Kato, Keiko Endo, Shotaro Yamano, Yasuharu Kanki, Yoshihiro Matsumura, Takashi Minami, Toshiya Tanaka, Motonobu Anai, Youichiro Wada, Hideki Wanibuchi, Mitsuhiro Hayashi, Akinobu Hamada, Masayuki Yoshida, Shinichi Yachida, Mitsuyoshi Nakao, Juro Sakai, Hiroyuki Aburatani, Masabumi Shibuya, Kentaro Hanada, Satoru Miyano, Tomoyoshi Soga, Tatsuhiko Kodama.

  Tolerance to severe tumor microenvironments, including hypoxia and nutrient starvation, is a common feature of aggressive cancer cells and can be targeted. However, metabolic alterations that support cancer cells upon nutrient starvation are not well understood. Here, by comprehensive metabolome analyses, we show that glutamine deprivation leads to phosphoethanolamine (PEtn) accumulation in cancer cells via the downregulation of PEtn cytidylyltransferase (PCYT2), a rate-limiting enzyme of phosphatidylethanolamine biosynthesis. PEtn accumulation correlated with tumor growth under nutrient starvation. PCYT2 suppression was partially mediated by downregulation of the transcription factor ELF3. Furthermore, PCYT2 overexpression reduced PEtn levels and tumor growth. In addition, PEtn accumulation and PCYT2 downregulation in human breast tumors correlated with poor prognosis. Thus, we show that glutamine deprivation leads to tumor progression by regulating PE biosynthesis via the ELF3-PCYT2 axis. Furthermore, manipulating glutamine-responsive genes could be a therapeutic approach to limit cancer progression.

Keywords:  PCYT2; PE biosynthesis; amino acids; cancer metabolism; glutamine deprivation; hypoxia; nutrient starvation; phosphoethanolamine; tumor microenvironments

DOI:  https://doi.org/10.1016/j.celrep.2019.08.087
Trends Analyt Chem. 2019 Sep;118 880-892

Recent advances in mass spectrometry (MS)-based glycoproteomics in complex biological samples.

Zhengwei Chen, Junfeng Huang, Lingjun Li.

  Protein glycosylation plays a key role in various biological processes and disease-related pathological progression. Mass spectrometry (MS)-based glycoproteomics is a powerful approach that provides a system-wide profiling of the glycoproteome in a high-throughput manner. There have been numerous significant technological advances in this field, including improved glycopeptide enrichment, hybrid fragmentation techniques, emerging specialized software packages, and effective quantitation strategies, as well as more dedicated workflows. With increasingly sophisticated glycoproteomics tools on hand, researchers have extensively adapted this approach to explore different biological systems both in terms of in-depth glycoproteome profiling and comparative glycoproteome analysis. Quantitative glycoproteomics enables researchers to discover novel glycosylation-based biomarkers in various diseases with potential to offer better sensitivity and specificity for disease diagnosis. In this review, we present recent methodological developments in MS-based glycoproteomics and highlight its utility and applications in answering various questions in complex biological systems.

Keywords:  Biological samples; Biomarker; Disease; Glycoproteomics; Mass spectrometry; N-Glycosylation; O-Glycosylation

DOI:  https://doi.org/10.1016/j.trac.2018.10.009
Methods Mol Biol. 2020 ;2064 135-146

Toward Single Cell Molecular Imaging by Matrix-Free Nanophotonic Laser Desorption Ionization Mass Spectrometry.

Sylwia A Stopka, Akos Vertes.

  In recent years, innovations in mass spectrometry imaging (MSI) have enabled simultaneous detection and mapping of biomolecules and xenobiotics directly from biological tissues and single cells. Matrix-assisted laser desorption ionization (MALDI) has been the most widely embraced MSI technique. However, this technique can exhibit ion suppression effects hindering metabolite coverage and possesses a narrow dynamic range. Nanophotonic platforms, e.g., silicon nanopost array (NAPA) structures, can be used as an alternative for matrix-free imaging of biological tissues. Here, we present a protocol for MSI of large and small adherent cell clusters by laser desorption ionization from NAPA with minimal sample preparation.

Keywords:  Cell clusters; Cell culture; Mass spectrometry imaging; Metabolites; Molecular imaging; NAPA; Nanopost array

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_11
Sci Rep. 2019 Oct 01. 9(1): 14114

The effect of high glucose on lipid metabolism in the human placenta.

Charlotte H Hulme, Anna Nicolaou, Sharon A Murphy, Alexander E P Heazell, Jenny E Myers, Melissa Westwood.

Diabetes mellitus (DM) during pregnancy can result in fetal overgrowth, likely due to placental dysfunction, which has health consequences for the infant. Here we test our prediction from previous work using a placental cell line that high glucose concentrations affect placental lipid metabolism. Placentas from women with type 1 (n = 13), type 2 (n = 6) or gestational (n = 12) DM, BMI-matched to mothers without DM (n = 18), were analysed for lipase and fatty acid transport proteins and fatty acid and triglyceride content. Explants from uncomplicated pregnancies (n = 6) cultured in physiological or high glucose were similarly analysed. High glucose levels did not alter placental lipase or transporter expression or the profile and abundance of fatty acids, but triglyceride levels were higher (p < 0.05), suggesting reduced β- oxidation. DM did not affect placental protein expression or fatty acid profile. Triglyceride levels of placentas from mothers with pre-existing DM were similar to controls, but higher in obese women with gestational DM. Maternal hyperglycemia may not affect placental fatty acid uptake and transport. However, placental β-oxidation is affected by high glucose and reduced in a subset of women with DM. Abnormal placental lipid metabolism could contribute to increased maternal-fetal lipid transfer and excess fetal growth in some DM pregnancies.

DOI: https://doi.org/10.1038/s41598-019-50626-x
Methods Mol Biol. 2020 ;2064 73-88

Applications of MicroArrays for Mass Spectrometry (MAMS) in Single-Cell Metabolomics.

Alfredo J Ibáñez, Ales Svatos.

  The metabolic network is the endpoint in the flow of information that begins with the "gene" and ends with "phenotype" (observable function) of the cell. Previously, due to the variety of metabolites analyzed inside cells, the metabolomic measurements were performed with samples including multiple cells. Unfortunately, this sampling process may mask important metabolic phenomena, such as cell-to-cell heterogeneity. For these studies, we must use analytical techniques that can robustly deliver reproducible results with single-cell sensitivity. In this chapter, we summarize laser-based methods for single-cell analysis and a novel approach of MicroArrays for Mass Spectrometry (or MAMS) is described in full detail. This particular type of microarrays was tailored for the study of cells grown in liquid medium using multiple-analytical read-outs, such as optical and laser desorption/ionization (LDI) or MALDI mass spectrometry.

Keywords:  Cell populations; Heterogeneity; Laser; MALDI; MAMS; Mass spectrometry; Metabolites; Microarray; Single cell

DOI:  https://doi.org/10.1007/978-1-4939-9831-9_6