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      Pharmacometabolomics of Meglumine Antimoniate in Patients With Cutaneous Leishmaniasis

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          Abstract

          Control of cutaneous leishmaniasis (CL) in the Americas is dependent on chemotherapy with parenteral pentavalent antimonials. High rates of treatment failure urge the search for predictive and prognostic markers of therapeutic responsiveness. In this study, we aimed to identify biomarkers of therapeutic response during treatment with meglumine antimoniate (MA). We conducted untargeted metabolomic profiling of plasma samples from CL patients (n = 39; 25 who cured and 14 who did not cure), obtained before and at the end of treatment. Exposure to MA induced metabolic perturbations primarily reflecting alteration in long-chain fatty acid β-oxidation and energy production. Allantoin, N-acetylglutamine, taurine, and pyruvate were significantly more abundant in samples from patients who responded to treatment, and were predictive and prognostic of treatment outcome in this patient cohort (AUC > 0.7). In an ex vivo model of infection, allantoin but not taurine enhanced the MA-dependent killing of intracellular Leishmania ( Viannia) panamensis. Our results support the participation of metabolites mediating antioxidant and wound healing responses in clinical cure of CL, revealing relationships between metabolism and immune responses in the outcome of antileishmanial treatment.

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          Most cited references32

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          IDEOM: an Excel interface for analysis of LC-MS-based metabolomics data.

          The application of emerging metabolomics technologies to the comprehensive investigation of cellular biochemistry has been limited by bottlenecks in data processing, particularly noise filtering and metabolite identification. IDEOM provides a user-friendly data processing application that automates filtering and identification of metabolite peaks, paying particular attention to common sources of noise and false identifications generated by liquid chromatography-mass spectrometry (LC-MS) platforms. Building on advanced processing tools such as mzMatch and XCMS, it allows users to run a comprehensive pipeline for data analysis and visualization from a graphical user interface within Microsoft Excel, a familiar program for most biological scientists. IDEOM is provided free of charge at http://mzmatch.sourceforge.net/ideom.html, as a macro-enabled spreadsheet (.xlsb). Implementation requires Microsoft Excel (2007 or later). R is also required for full functionality. michael.barrett@glasgow.ac.uk Supplementary data are available at Bioinformatics online.
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            PeakML/mzMatch: a file format, Java library, R library, and tool-chain for mass spectrometry data analysis.

            The recent proliferation of high-resolution mass spectrometers has generated a wealth of new data analysis methods. However, flexible integration of these methods into configurations best suited to the research question is hampered by heterogeneous file formats and monolithic software development. The mzXML, mzData, and mzML file formats have enabled uniform access to unprocessed raw data. In this paper we present our efforts to produce an equally simple and powerful format, PeakML, to uniformly exchange processed intermediary and result data. To demonstrate the versatility of PeakML, we have developed an open source Java toolkit for processing, filtering, and annotating mass spectra in a customizable pipeline (mzMatch), as well as a user-friendly data visualization environment (PeakML Viewer). The PeakML format in particular enables the flexible exchange of processed data between software created by different groups or companies, as we illustrate by providing a PeakML-based integration of the widely used XCMS package with mzMatch data processing tools. As an added advantage, downstream analysis can benefit from direct access to the full mass trace information underlying summarized mass spectrometry results, providing the user with the means to rapidly verify results. The PeakML/mzMatch software is freely available at http://mzmatch.sourceforge.net, with documentation, tutorials, and a community forum.
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              Toward global metabolomics analysis with hydrophilic interaction liquid chromatography-mass spectrometry: improved metabolite identification by retention time prediction.

              Metabolomics is an emerging field of postgenomic biology concerned with comprehensive analysis of small molecules in biological systems. However, difficulties associated with the identification of detected metabolites currently limit its application. Here we demonstrate that a retention time prediction model can improve metabolite identification on a hydrophilic interaction chromatography (HILIC)-high-resolution mass spectrometry metabolomics platform. A quantitative structure retention relationship (QSRR) model, incorporating six physicochemical variables in a multiple-linear regression based on 120 authentic standard metabolites, shows good predictive ability for retention times of a range of metabolites (cross-validated R(2) = 0.82 and mean squared error = 0.14). The predicted retention times improved metabolite identification by removing 40% of the false identifications that occurred with identification by accurate mass alone. The importance of this procedure was demonstrated by putative identification of 690 metabolites in extracts of the protozoan parasite Trypanosoma brucei, thus allowing identified metabolites to be mapped onto an organism-wide metabolic network, providing opportunities for future studies of cellular metabolism from a global systems biology perspective.
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                Author and article information

                Contributors
                URI : https://loop.frontiersin.org/people/687128
                URI : https://loop.frontiersin.org/people/238448
                URI : https://loop.frontiersin.org/people/343999
                URI : https://loop.frontiersin.org/people/497445
                URI : https://loop.frontiersin.org/people/280889
                Journal
                Front Pharmacol
                Front Pharmacol
                Front. Pharmacol.
                Frontiers in Pharmacology
                Frontiers Media S.A.
                1663-9812
                20 June 2019
                2019
                : 10
                : 657
                Affiliations
                [1] 1Centro Internacional de Entrenamiento e Investigaciones Médicas, CIDEIM , Cali, Colombia
                [2] 2Universidad de Valle , Cali, Colombia
                [3] 3Universidad ICESI , Cali, Colombia
                [4] 4Glasgow Polyomics, Wolfson Wohl Cancer Research Centre, College of Medical Veterinary & Life Sciences, University of Glasgow , Glasgow, United Kingdom
                [5] 5Institute of Infection, Immunity and Inflammation, College of Medical, Veterinary and Life Sciences, University of Glasgow , Glasgow, United Kingdom
                Author notes

                Edited by: Houkai Li, Shanghai University of Traditional Chinese Medicine, China

                Reviewed by: Ibrahim Khalifeh, American University of Beirut, Lebanon; Nazareno Paolocci, Johns Hopkins University, United States

                *Correspondence: María Adelaida Gómez, mgomez@ 123456cideim.org.co

                This article was submitted to Translational Pharmacology, a section of the journal Frontiers in Pharmacology

                Article
                10.3389/fphar.2019.00657
                6595045
                31281253
                fe18a47c-dd32-4368-ac14-19780547b8e2
                Copyright © 2019 Vargas, Prieto, Martínez-Valencia, Cossio, Burgess, Burchmore and Gómez

                This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

                History
                : 13 December 2018
                : 20 May 2019
                Page count
                Figures: 5, Tables: 2, Equations: 0, References: 50, Pages: 11, Words: 5478
                Funding
                Funded by: National Institute of Allergy and Infectious Diseases 10.13039/100000060
                Award ID: R01AI104823
                Funded by: Departamento Administrativo de Ciencia, Tecnología e Innovación 10.13039/100007637
                Award ID: 2229-65843177 , 0552 – 2015
                Funded by: Newton Fund 10.13039/100010897
                Award ID: 172715657
                Categories
                Pharmacology
                Original Research

                Pharmacology & Pharmaceutical medicine
                cutaneous leishmaniasis,meglumine antimoniate,pharmacometabolomics,biomarkers,allantoin,taurine

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