bims-oximas 2020-05-17 papers

bims-oximas

Biomed News

on Oxidative stress and mass spectrometry

Issue of 2020–05–17
twenty papers selected by
Alpesh Thakker, University of the Highlands and Islands

An Innovative Lipidomic Workflow to Investigate the Lipid Profile in a Cystic Fibrosis Cell Line.
The impact of extracellular fatty acids and oxygen tension on lipid synthesis and assembly in pancreatic cancer cells.
Introducing online multicolumn two-dimensional liquid chromatography screening for facile selection of stationary and mobile phase conditions in both dimensions.
Identification of short chain fatty acid esters of hydroxy fatty acids (SFAHFAs) in murine model by nontargeted analysis using ultra-high-performance liquid chromatography/linear trap quadrupole-Orbitrap mass spectrometry.
Triple Negative Breast Cancer Detection Using LC-MS/MS Lipidomic Profiling.
Metabolic Dysregulation of the Lysophospholipid/autotaxin Axis in the Chromosome 9p21 Gene SNP rs10757274.
Discovery of Eicosapentaenoic Acid Esters of Hydroxy Fatty Acids as Potent Nrf2 Activators.
BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.
A high-throughput mass spectrometry-based assay for large-scale profiling of circulating human apolipoproteins.
Reproducible molecular networking of untargeted mass spectrometry data using GNPS.
Lipid biosignature of breast cancer tissues by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.
Alterations in plasma triglycerides and ceramides: links with cardiac function in humans with type 2 diabetes.
MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics.
Isoprostanoids Levels in Cerebrospinal Fluid Do Not Reflect Alzheimer's Disease.
Integrative Biological Network Analysis to Identify Shared Genes in Metabolic Disorders.
15-Lipoxygenase-1 biosynthesis of 7S,14S-diHDHA implicates 15-Lipoxygenase-2 in biosynthesis of resolvin D5.
Retip: retention time prediction for compound annotation in untargeted metabolomics.
Applications of molecular networks in biomedicine.
MEPHAS: an interactive graphical user interface for medical and pharmaceutical statistical analysis with R and Shiny.
Systemic Redox Imbalance in Patients with Chronic Granulomatous Disease.

Cells. 2020 May 12. pii: E1197. [Epub ahead of print]9(5):

An Innovative Lipidomic Workflow to Investigate the Lipid Profile in a Cystic Fibrosis Cell Line.

Michele Dei Cas, Aida Zulueta, Alessandra Mingione, Anna Caretti, Riccardo Ghidoni, Paola Signorelli, Rita Paroni.

  Altered lipid metabolism has been associated to cystic fibrosis disease, which is characterized by chronic lung inflammation and various organs dysfunction. Here, we present the validation of an untargeted lipidomics approach based on high-resolution mass spectrometry aimed at identifying those lipid species that unequivocally sign CF pathophysiology. Of n.13375 mass spectra recorded on cystic fibrosis bronchial epithelial airways epithelial cells IB3, n.7787 presented the MS/MS data, and, after software and manual validation, the final number of annotated lipids was restricted to n.1159. On these lipids, univariate and multivariate statistical approaches were employed in order to select relevant lipids for cellular phenotype discrimination between cystic fibrosis and HBE healthy cells. In cystic fibrosis IB3 cells, a pervasive alteration in the lipid metabolism revealed changes in the classes of ether-linked phospholipids, cholesterol esters, and glycosylated sphingolipids. Through functions association, it was evidenced that lipids variation involves the moiety implicated in membrane composition, endoplasmic reticulum, mitochondria compartments, and chemical and biophysical lipids properties. This study provides a new perspective in understanding the pathogenesis of cystic fibrosis and strengthens the need to use a validated mass spectrometry-based lipidomics approach for the discovery of potential biomarkers and perturbed metabolism.

Keywords:  OMICS; biomarker; cell structure; cystic fibrosis; lipidomics; membrane composition; sphingolipid; untargeted analysis

DOI:  https://doi.org/10.3390/cells9051197
ACS Chem Biol. 2020 May 12.

The impact of extracellular fatty acids and oxygen tension on lipid synthesis and assembly in pancreatic cancer cells.

Daniel P Downes, Natalie A Daurio, David G McLaren, Paul Carrington, Stephen F Previs, Katharine B Williams.

Lipid oxidation and biosynthesis are crucial for cell survival, especially for rapidly proliferating cancer cells in a heterogeneous metabolic environment. Storage of high energy lipid reservoirs competitively advantages the cancer cell over non-neoplastic tissue. Disrupting lipid biosynthetic processes, through modulation of fatty acid (FA) esterification or de novo lipogenesis (DNL), is of interest in drug discovery. Mimicking the in vivo environment in vitro is also vital for testing the efficacy of potential drug compounds. We present here a stable isotope tracer-based approach for examining the impact of exogenous FA and oxygen tension on the pathways that affect lipid biosynthesis, including the rates of metabolic flux. By applying tandem mass spectrometry (MS/MS) analyses, to studies using parallel tracers, we characterized the impact of FA bioavailability on the positional enrichment within specific lipids. Our observations suggest that adding bioavailable FA as a carbon source preferentially biases the cellular metabolism away from DNL and towards esterification of free fatty acid pools. Additionally, we have found that this FA addition, under hypoxic conditions, led to biased increase in the total triglyceride pool (nearly 5-fold, as compared to phospholipids), regardless of the isotope tracer utilized. We discuss the implications of this metabolic flexibility on studies that aim to characterize apparent drug efficacy.

DOI: https://doi.org/10.1021/acschembio.0c00219
J Chromatogr A. 2020 Jan 16. pii: S0021-9673(20)30072-8. [Epub ahead of print] 460895

Introducing online multicolumn two-dimensional liquid chromatography screening for facile selection of stationary and mobile phase conditions in both dimensions.

Heather Wang, Hayley R Lhotka, Raffeal Bennett, Miraslava Potapenko, Chad J Pickens, Benjamin F Mann, Imad A Haidar Ahmad, Erik L Regalado.

  Baseline separation and analysis of multicomponent mixtures of closely related pharmaceuticals using single column selectivity can often be challenging, requiring the combination of orthogonal stationary and mobile phase methods to monitor all the species and optimize reaction outcomes. In recent years, two-dimensional liquid chromatography (2D-LC) has become a valuable tool for improving peak capacity and selectivity. Though powerful, standard 2D-LC instrumentation and software can often lead to tedious method development and has a requirement for very specific expertise that is poorly suited for a fast-paced industrial environment. In this regard, the introduction of an automated online 2D-LC setup that could screen multiple columns in both dimensions without manual intervention will undeniably serve to streamline column/mobile phase selection and secure the viability of 2D-LC as a mainstay instrument for industrial applications. Herein, we introduce and investigate a multicolumn online 2D-LC approach that simplifies column screening and method development dramatically. This setup incorporates 6-position column selection valve technology whose functionality enables us to combine multiple columns in the first and second dimensions. This strategy in conjunction with diode array detection (DAD) in both dimensions and mass spectrometry (MS) acquisition in the second dimension serves to explore different columns and mobile phases as a framework for screening targeted compounds in multicomponent mixtures without having to perform chromatographic purification. Multiple online heart cutting achiral RPLC - achiral RPLC and achiral RPLC - chiral RPLC coupled to DAD and ESI-MS methods combining several stationary phase selectivity in an automated fashion are successfully applied to the separation and analysis of complex mixtures of drug substances, where in many instances, traditional 1D-ultra-high performance liquid chromatography (UHPLC) fails or delivers sub-optimal results. This automated online multicolumn 2D-LC workflow enables rapid and efficient identification of column/eluent combinations, as well as sample analysis across multiple columns in both dimensions overnight with a single click.

Keywords:  Achiral and chiral separations; Automated multicolumn screening; Closely related species; Diode array detection- Mass spectrometry; Method development; Multicomponent mixtures; Two-dimensional liquid chromatography

DOI:  https://doi.org/10.1016/j.chroma.2020.460895
Rapid Commun Mass Spectrom. 2020 May 15.

Identification of short chain fatty acid esters of hydroxy fatty acids (SFAHFAs) in murine model by nontargeted analysis using ultra-high-performance liquid chromatography/linear trap quadrupole-Orbitrap mass spectrometry.

Siddabasave Gowda B Gowda, Chongsheng Liang, Divyavani Gowda, Fengjue Hou, Kentaro Kawakami, Satoru Fukiya, Atsushi Yokota, Hitoshi Chiba, Shu-Ping Hui.

RATIONALE: Fatty acid esters of hydroxy fatty acids (FAHFAs) are recently discovered endogenous lipids with outstanding health benefits. FAHFAs are known to exhibit antioxidant, antidiabetic and anti-inflammatory properties. The number of known long chain FAHFAs in mammalian tissues and dietary resources increased recently because of the latest developments in high-resolution tandem mass spectrometry techniques. However, there are no reports on the identification of short chain fatty acid esterified hydroxy fatty acids (SFAHFAs).
METHODS: Intestinal contents, tissues, and plasma of rats fed with high-fat diet (HFD) and normal diet (ND) were analysed for fatty acids, hydroxy fatty acids, and FAHFAs using ultra-high-performance liquid chromatography (UHPLC) and linear trap quadrupole-Orbitrap mass spectrometry (LTQ Orbitrap MS) with negative heated electrospray ionization.
RESULTS: Untargeted analysis of total lipid extracts from murine samples (male 13-week old WKAH/HKmSlc rats) led to the identification of several new SFAHFAs of acetic acid or propanoic acid esterified long chain (>C20)-hydroxy fatty acids. Furthermore, MS3 analysis revealed the position of the hydroxyl group in the long chain fatty acid as C-2. The relative amounts of SFAHFAs were quantified in intestinal contents and their tissues (caecum, small intestine, and large intestine), liver, and plasma of rats fed with HFD and ND. The large intestine showed the highest abundance of SFAHFAs with a concentration range from 0.84 to 57 pmoles/mg followed by the cecum with a range of 0.66 to 28.6 pmoles/mg. The SFAHFAs were significantly altered between the HFD and ND groups, with a strong decreasing tendency under HFD conditions.
CONCLUSIONS: Identification of these novel SFHFAs can contribute to better understanding the chemical and biological properties of individual SFHFAs and their possible sources in the gut, which in turn helps us tackle the role of these lipids in various metabolic diseases.

DOI: https://doi.org/10.1002/rcm.8831
J Proteome Res. 2020 May 13.

Triple Negative Breast Cancer Detection Using LC-MS/MS Lipidomic Profiling.

Ryan Eghlimi, Xiaojian Shi, Jonathan Hrovat, Bowei Xi, Haiwei Gu.

Breast cancer (BC) is a heterogeneous malignancy that is responsible for a great portion of female cancer cases and cancer-related deaths in the United States. In comparison to other major BC subtypes, triple negative breast cancer (TNBC) presents with a relatively low survival rate and a high rate of metastasis. This has led to a strong, though largely unmet, need for more sensitive and specific methods of early stage TNBC (ES-TNBC) detection to combat its high-grade pathology and relatively low survival rate. The current study employs a liquid chromatography-tandem mass spectrometry assay capable of targeted, highly specific and sensitive detection of lipids to propose two diagnostic biomarker panels for TNBC/ES-TNBC. Using this approach, 110 lipids were reliably detected in 166 human plasma samples, 45 controls and 121 BC (96 non-TNBC and 25 TNBC) subjects. Univariate and multivariate analyses allowed the construction and application of a 19-lipid biomarker panel capable of distinguishing TNBC (and ES-TNBC) from controls, as well as, a 5-lipid biomarker panel capable of differentiating TNBC from non-TNBC and ES-TNBC from ES-non-TNBC. Receiver operating characteristic curves with notable classification performances were generated from the biomarker panels according to their orthogonal partial least squares-discrimination analysis models. TNBC was distinguished from controls with an area under the receiving operating characteristic curve (AUROC) = 0.93, sensitivity = 0.96, specificity = 0.76, and ES-TNBC from controls with an AUROC = 0.96, sensitivity = 0.95, and specificity = 0.89. TNBC was differentiated from non-TNBC with an AUROC = 0.88, sensitivity = 0.88, specificity = 0.79, and ES-TNBC from ES-non-TNBC with an AUROC = 0.95, sensitivity = 0.95, and specificity = 0.87. A pathway enrichment analysis between TNBC and controls also revealed significant disturbances in choline metabolism, sphingolipid signaling, and glycerophospholipid metabolism. To the best of our knowledge, this is the first study to propose a diagnostic lipid biomarker panel for TNBC detection. All raw mass spectrometry data have been deposited to MassIVE (dataset identifier: MSV000085324).

DOI: https://doi.org/10.1021/acs.jproteome.0c00038
Circ Genom Precis Med. 2020 May 12.

Metabolic Dysregulation of the Lysophospholipid/autotaxin Axis in the Chromosome 9p21 Gene SNP rs10757274.

Sven W Meckelmann, Jade I Hawksworth, Daniel White, Robert Andrews, Patricia Rodrigues, Anne O'Connor, Jorge Alvarez-Jarreta, Victoria J Tyrrell, Christine Hinz, You Zhou, Julie Williams, Maceler Aldrovandi, William J Watkins, Adam J Engler, Valentina Lo Sardo, David A Slatter, Stuart M Allen, Jay Acharya, Jacquie Mitchell, Jackie Cooper, Junken Aoki, Kuniyuki Kano, Steve E Humphries, Valerie B O'Donnell.

  Background - Common chromosome 9p21 SNPs increase coronary heart disease (CHD) risk, independent of "traditional lipid risk factors". However, lipids comprise large numbers of structurally related molecules not measured in traditional risk measurements, and many have inflammatory bioactivities. Here we applied lipidomic and genomic approaches to three model systems, to characterize lipid metabolic changes in common Chr9p21 SNPs which confer ~30% elevated CHD risk associated with altered expression of ANRIL, a long ncRNA. Methods - Untargeted and targeted lipidomics was applied to plasma from Northwick Park Heart Study II (NPHSII) homozygotes for AA or GG in rs10757274, followed by correlation and network analysis. To identify candidate genes, transcriptomic data from shRNA downregulation of ANRIL in HEK293 cells was mined. Transcriptional data from vascular smooth muscle cells differentiated from iPSCs of individuals with/without Chr9p21 risk, non-risk alleles, and corresponding knockout isogenic lines were next examined. Last, an in-silico analysis of miRNAs was conducted to identify how ANRIL might control lysoPL/lysoPA genes. Results - Elevated risk GG correlated with reduced lysophosphospholipids (lysoPLs), lysophosphatidic acids (lysoPA) and autotaxin (ATX). Five other risk SNPs did not show this phenotype. LysoPL-lysoPA interconversion was uncoupled from ATX in GG plasma, suggesting metabolic dysregulation. Significantly altered expression of several lysoPL/lysoPA metabolising enzymes was found in HEK cells lacking ANRIL. In the VSMC dataset, the presence of risk alleles associated with altered expression of several lysoPL/lysoPA enzymes. Deletion of the risk locus reversed expression of several lysoPL/lysoPA genes to non-risk haplotype levels. Genes that were altered across both cell datasets were DGKA, MBOAT2, PLPP1 and LPL. The in-silico analysis identified four ANRIL-regulated miRNAs that control lysoPL genes as miR-186-3p, miR-34a-3p, miR-122-5p, miR-34a-5p. Conclusions - A Chr9p21 risk SNP associates with complex alterations in immune-bioactive phospholipids and their metabolism. Lipid metabolites and genomic pathways associated with CHD pathogenesis in Chr9p21 and ANRIL-associated disease are demonstrated.

Keywords:  phospholipids

DOI:  https://doi.org/10.1161/CIRCGEN.119.002806
Antioxidants (Basel). 2020 May 08. pii: E397. [Epub ahead of print]9(5):

Discovery of Eicosapentaenoic Acid Esters of Hydroxy Fatty Acids as Potent Nrf2 Activators.

Siddabasave Gowda B Gowda, Hirotoshi Fuda, Takayuki Tsukui, Hitoshi Chiba, Shu-Ping Hui.

  Branched fatty acid esters of hydroxy fatty acids (FAHFAs) are a recently discovered class of biologically active lipids with anti-inflammatory and anti-diabetic properties. Despite the possible link between endogenous FAHFA levels and nuclear factor erythroid 2-related factor 2 (Nrf2), their possible function as antioxidants and the mechanisms involved in this are unknown. Here, we investigate FAHFAs' plausible antioxidant potential with reference to their effect on the Nrf2 levels, oxidative stress, and lipid droplet oxidation in human hepatocytes (C3A). Six authentic FAHFAs were chemically synthesized and performed activity-based screening by reporter gene assay. Among them, eicosapentaenoic acid (EPA) esterified 12-hydroxy stearic acid (12-HSA) and 12-hydroxy oleic acid (12-HOA) FAHFAs showed less cytotoxicity compared to their free fatty acids and potent activators of Nrf2. To define their mode of action, relative levels of nuclear Nrf2 were determined, which found a higher amount of Nrf2 in nucleus of cells treated with 12-EPAHSA compared to the control. Furthermore, 12-EPAHSA increased the expression of Nrf2-dependent antioxidant enzyme genes (NQO1, GCLM, GCLC, SOD-1, and HO-1). Fluorescence imaging analysis of linoleic-acid-induced lipid droplets (LDs) in C3A cells treated with 12-EPAHSA revealed the strong inhibition of small-size LD oxidation. These results suggest that EPA-derived FAHFAs as a new class of lipids with less cytotoxicity, and strong Nrf2 activators with plausible antioxidant effects via the induction of cytoprotective proteins against oxidative stress, induced cellular damage.

Keywords:  EPA; Nrf2; antioxidants; lipid biochemistry; lipid droplet; lipid mediators; lipid synthesis; reporter gene assay

DOI:  https://doi.org/10.3390/antiox9050397
Nucleic Acids Res. 2020 May 11. pii: gkaa332. [Epub ahead of print]

BIOMEX: an interactive workflow for (single cell) omics data interpretation and visualization.

Federico Taverna, Jermaine Goveia, Tobias K Karakach, Shawez Khan, Katerina Rohlenova, Lucas Treps, Abhishek Subramanian, Luc Schoonjans, Mieke Dewerchin, Guy Eelen, Peter Carmeliet.

The amount of biological data, generated with (single cell) omics technologies, is rapidly increasing, thereby exacerbating bottlenecks in the data analysis and interpretation of omics experiments. Data mining platforms that facilitate non-bioinformatician experimental scientists to analyze a wide range of experimental designs and data types can alleviate such bottlenecks, aiding in the exploration of (newly generated or publicly available) omics datasets. Here, we present BIOMEX, a browser-based software, designed to facilitate the Biological Interpretation Of Multi-omics EXperiments by bench scientists. BIOMEX integrates state-of-the-art statistical tools and field-tested algorithms into a flexible but well-defined workflow that accommodates metabolomics, transcriptomics, proteomics, mass cytometry and single cell data from different platforms and organisms. The BIOMEX workflow is accompanied by a manual and video tutorials that provide the necessary background to navigate the interface and get acquainted with the employed methods. BIOMEX guides the user through omics-tailored analyses, such as data pretreatment and normalization, dimensionality reduction, differential and enrichment analysis, pathway mapping, clustering, marker analysis, trajectory inference, meta-analysis and others. BIOMEX is fully interactive, allowing users to easily change parameters and generate customized plots exportable as high-quality publication-ready figures. BIOMEX is open source and freely available at https://www.vibcancer.be/software-tools/biomex.

DOI: https://doi.org/10.1093/nar/gkaa332
J Lipid Res. 2020 May 13. pii: jlr.D120000835. [Epub ahead of print]

A high-throughput mass spectrometry-based assay for large-scale profiling of circulating human apolipoproteins.

Valentin Blanchard, Damien Garçon, Catherine Jaunet, Kevin Chemello, Stephanie Billon-Crossouard, Audrey Aguesse, Aya Garfa, Gilles Famchon, Amada Torres, Cedric Le May, Matthieu Pichelin, Edith Bigot-Corbel, Gilles Lambert, Bertrand Cariou, Samy Hadjadj, Michel Krempf, Kalyane Bach-Ngohou, Mikaël Croyal.

  Apolipoproteins govern lipoprotein metabolism and are promising biomarkers of metabolic and cardiovascular diseases. Unlike immunoassays, mass spectrometry enables the quantification and phenotyping of multiple apolipoproteins. Hence, here we aimed to develop an LC-MS/MS assay that can simultaneously quantitate 18 human apolipoproteins [A-I, A-II, A-IV, A-V, B48, B100, C-I, C-II, C-III, C-IV, D, E, F, H, J, L1, M, and (a)] and determined apoE, apoL1, and apo(a) phenotypes in human plasma and serum samples. The plasma and serum apolipoproteins were trypsin digested through an optimized procedure and peptides were extracted and analyzed by LC-MS/MS. The method was validated according to standard guidelines in samples spiked with known peptide amounts. The LC-MS/MS results were compared with those obtained with other techniques, and reproducibility, dilution effects, and stabilities were also assessed. Peptide markers were successfully selected for targeted apolipoprotein quantification and phenotyping. After optimization, the assay was validated for linearity, lower limits of quantification, accuracy (biases: -14.8% to 12.1%), intra-assay variability (CVs: 1.5%-14.2%), and inter-assay repeatability (CVs: 4.1%-14.3%). Bland-Altman plots indicated no major statistically significant differences between LC-MS/MS and other techniques. The LC-MS/MS results were reproducible over five repeated experiments (CVs: 1.8%-13.7%), and we identified marked differences among the plasma and serum samples. The LC-MS/MS assay developed here is rapid, requires only small sampling volumes, and incurs reasonable costs, thus making it amenable for a wide range of studies of apolipoprotein metabolism. We also highlight how this assay can be implemented in laboratories.

Keywords:  Apolipoproteins; Assay development; Cardiovascular diseases; Lipoproteins; Mass spectrometry; Metabolic diseases; Physical biochemistry; Proteomics; biomarkers; lipid metabolism

DOI:  https://doi.org/10.1194/jlr.D120000835
Nat Protoc. 2020 May 13.

Reproducible molecular networking of untargeted mass spectrometry data using GNPS.

Allegra T Aron, Emily C Gentry, Kerry L McPhail, Louis-Félix Nothias, Mélissa Nothias-Esposito, Amina Bouslimani, Daniel Petras, Julia M Gauglitz, Nicole Sikora, Fernando Vargas, Justin J J van der Hooft, Madeleine Ernst, Kyo Bin Kang, Christine M Aceves, Andrés Mauricio Caraballo-Rodríguez, Irina Koester, Kelly C Weldon, Samuel Bertrand, Catherine Roullier, Kunyang Sun, Richard M Tehan, Cristopher A Boya P, Martin H Christian, Marcelino Gutiérrez, Aldo Moreno Ulloa, Javier Andres Tejeda Mora, Randy Mojica-Flores, Johant Lakey-Beitia, Victor Vásquez-Chaves, Yilue Zhang, Angela I Calderón, Nicole Tayler, Robert A Keyzers, Fidele Tugizimana, Nombuso Ndlovu, Alexander A Aksenov, Alan K Jarmusch, Robin Schmid, Andrew W Truman, Nuno Bandeira, Mingxun Wang, Pieter C Dorrestein.

Global Natural Product Social Molecular Networking (GNPS) is an interactive online small molecule-focused tandem mass spectrometry (MS2) data curation and analysis infrastructure. It is intended to provide as much chemical insight as possible into an untargeted MS2 dataset and to connect this chemical insight to the user's underlying biological questions. This can be performed within one liquid chromatography (LC)-MS2 experiment or at the repository scale. GNPS-MassIVE is a public data repository for untargeted MS2 data with sample information (metadata) and annotated MS2 spectra. These publicly accessible data can be annotated and updated with the GNPS infrastructure keeping a continuous record of all changes. This knowledge is disseminated across all public data; it is a living dataset. Molecular networking-one of the main analysis tools used within the GNPS platform-creates a structured data table that reflects the molecular diversity captured in tandem mass spectrometry experiments by computing the relationships of the MS2 spectra as spectral similarity. This protocol provides step-by-step instructions for creating reproducible, high-quality molecular networks. For training purposes, the reader is led through a 90- to 120-min procedure that starts by recalling an example public dataset and its sample information and proceeds to creating and interpreting a molecular network. Each data analysis job can be shared or cloned to disseminate the knowledge gained, thus propagating information that can lead to the discovery of molecules, metabolic pathways, and ecosystem/community interactions.

DOI: https://doi.org/10.1038/s41596-020-0317-5
Breast Cancer Res Treat. 2020 May 15.

Lipid biosignature of breast cancer tissues by matrix-assisted laser desorption/ionization time-of-flight mass spectrometry.

Catarina L Silva, Rosa Perestrelo, Ivo Sousa-Ferreira, Filipa Capelinha, José S Câmara, Marijana Petković.

   PURPOSE: One of the hallmarks of cancer cells is the demand of supply for the synthesis of new membranes involved in cell proliferation and lipids have an important role in cellular structure, signaling pathways and progression of cancer. In this sense, lipid studies have become an essential tool allowing the establishment of signatures associated with breast cancer (BC). In this regard, some metabolic processes including proteins, nucleic acids and lipid synthesis are enhanced as part of cancer-associated metabolic reprogramming, as a requirement for cell growth and proliferation.
METHODS: Pairwise samples of breast active carcinoma (BAC) and breast cancer-free tissues were collected from n = 28 patients and analyzed by MALDI-TOF MS.
RESULTS: Major lipid species are identified in the MALDI-TOF mass spectra, with certain phosphatidylinositols (PIs) detectable only in BAC. Statistical analysis revealed significant differences (p < 0.05) between ratios lysophosphatidylcholine (LPC) 16:0/phosphatidylcholine (PC) 16:0_18:2 between AC and CF groups as well as for BC stages II and III. The ratio PC 16:0_18:2/PC16:0_18:1 was statistically different between AC and CF groups. The one-way ANOVA revealed that there are no statistical differences among BC stages (I, II and III) within AC group. Comparing BC stages, the significance impact increased (p < 0.05) with stage.
CONCLUSION: The obtained data revealed MALDI-TOF MS as a powerful tool to explore lipid signatures and the enzyme activity associated with BC and possibly establish novel disease markers.

Keywords:  Breast cancer; Glycerophosphocholine; Lipids; MALDI-TOF MS; Tissue

DOI:  https://doi.org/10.1007/s10549-020-05672-9
J Lipid Res. 2020 May 11. pii: jlr.RA120000669. [Epub ahead of print]

Alterations in plasma triglycerides and ceramides: links with cardiac function in humans with type 2 diabetes.

Linda R Peterson, Xuntian Jiang, Ling Chen, Anne C Goldberg, Marsha S Farmer, Daniel S Ory, Jean E Schaffer.

  Cardiac dysfunction in type 2 diabetes (T2D) is associated with excessive fatty acid uptake, oxidation, and generation of toxic lipid species by the heart. It is not known whether decreasing lipid delivery to the heart can effect improvement in cardiac function in humans with T2D. Thus, our objective was to test the hypothesis that lowering lipid delivery to the heart would result in evidence of decreased 'lipotoxicity' - improved cardiac function, and salutary effects on plasma biomarkers of cardiovascular risk. Thus, we performed a double-blind, randomized, placebo-controlled, parallel design study of the effects of 12 weeks of fenofibrate-induced lipid-lowering on cardiac function, inflammation and oxidation biomarkers, and on the ratio of two plasma ceramides - Cer d18:1 (4E) (1OH, 3OH)/24:0 and Cer d18:1 (4E) (1OH, 3OH)/16:0 - (i.e., 'C24:0/C16:0'), which is associated with decreased risk of cardiac dysfunction and heart failure. Fenofibrate lowered plasma TG and cholesterol but did not improve heart systolic or diastolic function. Fenofibrate treatment lowered the plasma C24:0/C16:0 ceramide ratio and minimally altered oxidative stress markers but did not alter measures of inflammation. Overall, plasma TG lowering correlated with improvement of cardiac relaxation (diastolic function) as measured by tissue Doppler-derived parameter é. Moreover, lowering the plasma C24:0/C16:0 ceramide ratio was correlated with worse diastolic function. These findings indicate that fenofibrate treatment per se is not sufficient to effect changes in cardiac function; however, decreases in plasma TG may be linked to improved diastolic function. In contrast, decreases in plasma C24:0/C16:0 are linked with worsening cardiac function.

Keywords:  Ceramides; Diabetes; Lipid treatment; Lipidomics; Lipotoxicity; Triglycerides

DOI:  https://doi.org/10.1194/jlr.RA120000669
Metabolites. 2020 May 07. pii: E186. [Epub ahead of print]10(5):

MetaboAnalystR 3.0: Toward an Optimized Workflow for Global Metabolomics.

Zhiqiang Pang, Jasmine Chong, Shuzhao Li, Jianguo Xia.

  Liquid chromatography coupled to high-resolution mass spectrometry platforms are increasingly employed to comprehensively measure metabolome changes in systems biology and complex diseases. Over the past decade, several powerful computational pipelines have been developed for spectral processing, annotation, and analysis. However, significant obstacles remain with regard to parameter settings, computational efficiencies, batch effects, and functional interpretations. Here, we introduce MetaboAnalystR 3.0, a significantly improved pipeline with three key new features: (1) efficient parameter optimization for peak picking; (2) automated batch effect correction; and 3) more accurate pathway activity prediction. Our benchmark studies showed that this workflow was 20~100X faster compared to other well-established workflows and produced more biologically meaningful results. In summary, MetaboAnalystR 3.0 offers an efficient pipeline to support high-throughput global metabolomics in the open-source R environment.

Keywords:  batch effects; global metabolomics; pathway activity prediction; peak detection

DOI:  https://doi.org/10.3390/metabo10050186
Antioxidants (Basel). 2020 May 10. pii: E407. [Epub ahead of print]9(5):

Isoprostanoids Levels in Cerebrospinal Fluid Do Not Reflect Alzheimer's Disease.

Carmen Peña-Bautista, Miguel Baquero, Marina López-Nogueroles, Máximo Vento, David Hervás, Consuelo Cháfer-Pericás.

  Previous studies showed a relationship between lipid oxidation biomarkers from plasma samples and Alzheimer's Disease (AD), constituting a promising diagnostic tool. In this work we analyzed whether these plasma biomarkers could reflect specific brain oxidation in AD. In this work lipid peroxidation compounds were determined in plasma and cerebrospinal fluid (CSF) samples from AD and non-AD (including other neurological pathologies) participants, by means of an analytical method based on liquid chromatography coupled with mass spectrometry. Statistical analysis evaluated correlations between biological matrices. The results did not show satisfactory correlations between plasma and CSF samples for any of the studied lipid peroxidation biomarkers (isoprostanes, neuroprostanes, prostaglandines, dihomo-isoprostanes). However, some of the analytes showed correlations with specific CSF biomarkers for AD and with neuropsychological tests (Mini-Mental State Examination (MMSE), Repeatable Battery for the Assessment of Neuropsychological Status (RBANS)). In conclusion, lipid peroxidation biomarkers in CSF samples do not reflect their levels in plasma samples, and no significant differences were observed between participant groups. However, some of the analytes could be useful as cognitive decline biomarkers.

Keywords:  Alzheimer’s disease; biomarker; blood-brain barrier; cerebrospinal fluid; lipid peroxidation; mass spectrometry

DOI:  https://doi.org/10.3390/antiox9050407
IEEE/ACM Trans Comput Biol Bioinform. 2020 May 08.

Integrative Biological Network Analysis to Identify Shared Genes in Metabolic Disorders.

Samet Tenekeci, Zerrin Isik.

Identification of common molecular mechanisms in interrelated diseases is essential for better prognoses and targeted therapies. However, complexity of metabolic pathways makes it difficult to discover common disease genes underlying metabolic disorders; and it requires more sophisticated bioinformatics models that combine different types of biological data and computational methods. Accordingly, we built an integrative network analysis model to identify shared disease genes in metabolic syndrome (MS), type 2 diabetes (T2D), and coronary artery disease (CAD). We constructed weighted gene co-expression networks by combining gene expression, protein-protein interaction, and gene ontology data from multiple sources. For 90 different configurations of disease networks, we detected the significant modules by using MCL, SPICi, and Linkcomm graph clustering algorithms. We also performed a comparative evaluation on disease modules to determine the best method providing the highest biological validity. By overlapping the disease modules, we identified 22 shared genes for MS-CAD and T2D-CAD. Moreover, 19 out of these genes were directly or indirectly associated with relevant diseases in the previous medical studies. This study does not only demonstrate the performance of different biological data sources and computational methods in disease-gene discovery, but also offers potential insights into common genetic mechanisms of the metabolic disorders.

DOI: https://doi.org/10.1109/TCBB.2020.2993301
J Lipid Res. 2020 May 13. pii: jlr.RA120000777. [Epub ahead of print]

15-Lipoxygenase-1 biosynthesis of 7S,14S-diHDHA implicates 15-Lipoxygenase-2 in biosynthesis of resolvin D5.

Steven C Perry, Chakrapani Kalyanaraman, Benjamin E Tourdot, William S Conrad, Oluwayomi Akinkugbe, John Cody Freedman, Michael Holinstat, Matthew P Jacobson, Theodore R Holman.

  The two oxylipins 7S,14S-dihydroxydocosahexaenoic acid (-diHDHA) and 7S,17S-diHDHA (resolvin D5 [RvD5]) have been found in macrophages and infectious inflammatory exudates and are believed to function as specialized pro-resolving mediators (SPMs). Their biosynthesis is thought to proceed through sequential oxidations of docosahexaenoic acid (DHA) by lipoxygenase enzymes, specifically, by human 5-lipoxygenase (h5-LOX) first to 7S-HDHA, followed by h12-LOX to form 7S,14S-diHDHA or h15-LOX-1 to form RvD5. In this work, we determined that oxidation of 7S-HpDHA to 7S,14S-diHDHA is performed with similar kinetics by either h12-LOX or h15-LOX-1. The oxidation at C14 of DHA by h12-LOX was expected, but the non-canonical reaction of h15-LOX-1 to make over 80% 7S,14S-diHDHA was larger than expected. Results of computer modeling suggested that the alcohol on C7 of 7S-HDHA hydrogen bonds with the backbone carbonyl of Ile-399, forcing the hydrogen abstraction from C12 to oxygenate on C14, and not C17. This result raised questions regarding the synthesis of RvD5. Strikingly, we found that h15-LOX-2 oxygenates 7S-HDHA almost exclusively at C17, forming RvD5 with faster kinetics than does h15-LOX-1. The presence of h15-LOX-2 in neutrophils and macrophages suggests that it may have a greater role in biosynthesizing SPMs than previously thought. We also determined that the reactions of h5-LOX with 14S-HpDHA and 17S-HpDHA are kinetically slow compared with DHA, suggesting that these reactions may be minor biosynthetic routes in vivo. Additionally, we show that 7S,14S-diHDHA and RvD5 have anti-aggregation properties with platelets at low micromolar potencies, which could directly regulate clot resolution.

Keywords:  Enzymology/Enzyme mechanisms; Enzymology/Enzyme regulation; Fatty acid; Fatty acid/Oxidation; Fish oil; Inflammation; Lipoxygenase; oxylipin; oxylipin biosynthesis; resolving d5

DOI:  https://doi.org/10.1194/jlr.RA120000777
Anal Chem. 2020 May 10.

Retip: retention time prediction for compound annotation in untargeted metabolomics.

Paolo Bonini, Tobias Kind, Hiroshi Tsugawa, Dinesh Kumar Barupal, Oliver Fiehn.

Unidentified peaks remain a major problem in untargeted metabolomics by LC-MS/MS. Confidence in peak annotations increases by combining MS/MS matching and retention time. We here show how retention times can be predicted from molecular structures. Two large, publicly available datasets were used for model training in machine learning: the Fiehn hydrophilic interaction liquid chromatography dataset (HILIC) of 981 primary metabolites and biogenic amines, and the RIKEN Plant Specialized Metabolome Annotation (PlaSMA) database of 852 secondary metabolites that uses reversed-phase liquid chromatography (RPLC). Five different machine learning algorithms have been integrated into the Retip R package: the random forest, Bayesian-regularized neural network, XGBoost, light gradient-boosting machine (LightGBM) and Keras algorithms for building the retention time prediction models. A complete workflow for retention time prediction was developed in R. It can be freely downloaded from the GitHub repository (https://www.retip.app). Keras outperformed other machine learning algorithms in the test set with minimum overfitting, verified by small error differences between training, test and validation sets. Keras yielded a mean absolute error (MAE) of 0.78 minutes for HILIC and 0.57 minutes for RPLC. Retip is integrated into the mass spectrometry software tools MS-DIAL and MS-FINDER, allowing a complete compound annotation workflow. In a test application on mouse blood plasma samples, we found a 68% reduction in the number of candidate structures when searching all isomers in MS-FINDER compound identification software. Retention time prediction increases the identification rate in liquid chromatography and subsequently leads to an improved biological interpretation of metabolomics data.

DOI: https://doi.org/10.1021/acs.analchem.9b05765
Biol Methods Protoc. 2019 ;4(1): bpz012

Applications of molecular networks in biomedicine.

Monica Chagoyen, Juan A G Ranea, Florencio Pazos.

  Due to the large interdependence between the molecular components of living systems, many phenomena, including those related to pathologies, cannot be explained in terms of a single gene or a small number of genes. Molecular networks, representing different types of relationships between molecular entities, embody these large sets of interdependences in a framework that allow their mining from a systemic point of view to obtain information. These networks, often generated from high-throughput omics datasets, are used to study the complex phenomena of human pathologies from a systemic point of view. Complementing the reductionist approach of molecular biology, based on the detailed study of a small number of genes, systemic approaches to human diseases consider that these are better reflected in large and intricate networks of relationships between genes. These networks, and not the single genes, provide both better markers for diagnosing diseases and targets for treating them. Network approaches are being used to gain insight into the molecular basis of complex diseases and interpret the large datasets associated with them, such as genomic variants. Network formalism is also suitable for integrating large, heterogeneous and multilevel datasets associated with diseases from the molecular level to organismal and epidemiological scales. Many of these approaches are available to nonexpert users through standard software packages.

Keywords:  biological networks; human pathologies; systems medicine

DOI:  https://doi.org/10.1093/biomethods/bpz012
BMC Bioinformatics. 2020 May 11. 21(1): 183

MEPHAS: an interactive graphical user interface for medical and pharmaceutical statistical analysis with R and Shiny.

Yi Zhou, Siu-Wai Leung, Shosuke Mizutani, Tatsuya Takagi, Yu-Shi Tian.

   BACKGROUND: Even though R is one of the most commonly used statistical computing environments, it lacks a graphical user interface (GUI) that appeals to students, researchers, lecturers, and practitioners in medicine and pharmacy for conducting standard data analytics. Current GUIs built on top of R, such as EZR and R-Commander, aim to facilitate R coding and visualization, but most of the functionalities are still accessed through a command-line interface (CLI). To assist practitioners of medicine and pharmacy and researchers to run most routines in fundamental statistical analysis, we developed an interactive GUI; i.e., MEPHAS, to support various web-based systems that are accessible from laptops, workstations, or tablets, under Windows, macOS (and IOS), or Linux. In addition to fundamental statistical analysis, advanced statistics such as the extended Cox regression and dimensional analyses including partial least squares regression (PLS-R) and sparse partial least squares regression (SPLS-R), are also available in MEPHAS.
RESULTS: MEPHAS is a web-based GUI (https://alain003.phs.osaka-u.ac.jp/mephas/) that is based on a shiny framework. We also created the corresponding R package mephas (https://mephas.github.io/). Thus far, MEPHAS has supported four categories of statistics, including probability, hypothesis testing, regression models, and dimensional analyses. Instructions and help menus were accessible during the entire analytical process via the web-based GUI, particularly advanced dimensional data analysis that required much explanation. The GUI was designed to be intuitive for non-technical users to perform various statistical functions, e.g., managing data, customizing plots, setting parameters, and monitoring real-time results, without any R coding from users. All generated graphs can be saved to local machines, and tables can be downloaded as CSV files.
CONCLUSION: MEPHAS is a free and open-source web-interactive GUI that was designed to support statistical data analyses and prediction for medical and pharmaceutical practitioners and researchers. It enables various medical and pharmaceutical statistical analyses through interactive parameter settings and dynamic visualization of the results.

Keywords:  Data analysis; Medical statistics; Partial least squares; Statistical software

DOI:  https://doi.org/10.1186/s12859-020-3494-x
J Clin Med. 2020 May 09. pii: E1397. [Epub ahead of print]9(5):

Systemic Redox Imbalance in Patients with Chronic Granulomatous Disease.

Edyta Heropolitanska-Pliszka, Klaudia Berk, Mateusz Maciejczyk, Jolanta Sawicka-Powierza, Ewa Bernatowska, Beata Wolska-Kusnierz, Malgorzata Pac, Nel Dabrowska-Leonik, Barbara Piatosa, Aleksandra Lewandowicz-Uszynska, Joanna Karpinska, Anna Zalewska, Bozena Mikoluc.

  The aim of our study was to evaluate redox status, enzymatic and non-enzymatic antioxidant barriers, oxidative damage of proteins, lipids and DNA, as well as concentration of coenzyme Q10 and vitamins A and E in patients with chronic granulomatous disease (CGD). The study was performed on fifteen Caucasian individuals (median age 24 years and seven months) diagnosed with CGD. The mutation in the NCF1 gene was confirmed in ten patients, and in the CYBB gene in five patients. We demonstrated high levels of total oxidant status (TOS) and oxidative stress index (OSI), lipids (↑8-isoprostanes (8-isoP), ↑4-hydroxynonenal (4-HNE)), proteins (↑advanced oxidation protein products (AOPP)) and DNA (↑8-hydroxy-2'-deoxyguanosine (8-OHdG)) oxidation products in CGD individuals as compared to sex- and age-matched healthy controls. We showed enhanced serum enzymatic activity of catalase (CAT) and superoxide dismutase-1 (SOD) and significantly decreased coenzyme Q10 concentration. Our study confirmed redox disturbances and increased oxidative damage in CGD patients, and indicated the need to compare redox imbalance depending on the type of mutation and nicotinamide adenine dinucleotide phosphate (NADPH) oxidase activity. The question regarding effectiveness of antioxidant therapy in patients with CGD is open, and the need to establish guidelines in this area remains to be addressed.

Keywords:  antioxidants; chronic granulomatous disease; coenzyme Q10; oxidative stress; primary immunodeficiency

DOI:  https://doi.org/10.3390/jcm9051397