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      Identification of serum metabolites associating with chronic kidney disease progression and anti-fibrotic effect of 5-methoxytryptophan

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          Abstract

          Early detection and accurate monitoring of chronic kidney disease (CKD) could improve care and retard progression to end-stage renal disease. Here, using untargeted metabolomics in 2155 participants including patients with stage 1–5 CKD and healthy controls, we identify five metabolites, including 5-methoxytryptophan (5-MTP), whose levels strongly correlate with clinical markers of kidney disease. 5-MTP levels decrease with progression of CKD, and in mouse kidneys after unilateral ureteral obstruction (UUO). Treatment with 5-MTP ameliorates renal interstitial fibrosis, inhibits IκB/NF-κB signaling, and enhances Keap1/Nrf2 signaling in mice with UUO or ischemia/reperfusion injury, as well as in cultured human kidney cells. Overexpression of tryptophan hydroxylase-1 (TPH-1), an enzyme involved in 5-MTP synthesis, reduces renal injury by attenuating renal inflammation and fibrosis, whereas TPH-1 deficiency exacerbates renal injury and fibrosis by activating NF-κB and inhibiting Nrf2 pathways. Together, our results suggest that TPH-1 may serve as a target in the treatment of CKD.

          Abstract

          Accurate monitoring of chronic kidney disease (CKD) progression is essential for efficient disease management. Here Chen et al. identify five serum metabolites in patients with stage 1–5 CKD whose levels associate with disease progression, and find that 5-methoxytryptophan and its regulatory enzyme TPH-1 exert anti-fibrotic effects in mouse models of kidney injury.

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          The random subspace method for constructing decision forests

          Tin Ho (1998)
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            Global metabolic profiling procedures for urine using UPLC-MS.

            The production of 'global' metabolite profiles involves measuring low molecular-weight metabolites (<1 kDa) in complex biofluids/tissues to study perturbations in response to physiological challenges, toxic insults or disease processes. Information-rich analytical platforms, such as mass spectrometry (MS), are needed. Here we describe the application of ultra-performance liquid chromatography-MS (UPLC-MS) to urinary metabolite profiling, including sample preparation, stability/storage and the selection of chromatographic conditions that balance metabolome coverage, chromatographic resolution and throughput. We discuss quality control and metabolite identification, as well as provide details of multivariate data analysis approaches for analyzing such MS data. Using this protocol, the analysis of a sample set in 96-well plate format, would take ca. 30 h, including 1 h for system setup, 1-2 h for sample preparation, 24 h for UPLC-MS analysis and 1-2 h for initial data processing. The use of UPLC-MS for metabolic profiling in this way is not faster than the conventional HPLC-based methods but, because of improved chromatographic performance, provides superior metabolome coverage.
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              Global metabolic profiling of animal and human tissues via UPLC-MS.

              Obtaining comprehensive, untargeted metabolic profiles for complex solid samples, e.g., animal tissues, requires sample preparation and access to information-rich analytical methodologies such as mass spectrometry (MS). Here we describe a practical two-step process for tissue samples that is based on extraction into 'aqueous' and 'organic' phases for polar and nonpolar metabolites. Separation methods such as ultraperformance liquid chromatography (UPLC) in combination with MS are needed to obtain sufficient resolution to create diagnostic metabolic profiles and identify candidate biomarkers. We provide detailed protocols for sample preparation, chromatographic procedures, multivariate analysis and metabolite identification via tandem MS (MS/MS) techniques and high-resolution MS. By using these optimized approaches, analysis of a set of samples using a 96-well plate format would take ~48 h: 1 h for system setup, 8-10 h for sample preparation, 34 h for UPLC-MS analysis and 2-3 h for preliminary/exploratory data processing, representing a robust method for untargeted metabolic screening of tissue samples.
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                Author and article information

                Contributors
                YaGuo@salud.unm.edu
                zyy@nwu.edu.cn
                Journal
                Nat Commun
                Nat Commun
                Nature Communications
                Nature Publishing Group UK (London )
                2041-1723
                1 April 2019
                1 April 2019
                2019
                : 10
                : 1476
                Affiliations
                [1 ]ISNI 0000 0004 1761 5538, GRID grid.412262.1, Faculty of Life Science & Medicine, , Northwest University, ; No. 229 Taibai North Road, Xi’an, Shaanxi 710069 China
                [2 ]ISNI 0000 0000 8744 8924, GRID grid.268505.c, School of Pharmacy, , Zhejiang Chinese Medical University, ; No. 548 Binwen Road, Hangzhou, Zhejiang 310053 China
                [3 ]ISNI 0000 0001 2188 8502, GRID grid.266832.b, Department of Internal Medicine, , University of New Mexico, ; 1700 Lomas Blvd NE, Albuquerque, New Mexico 87131 USA
                [4 ]GRID grid.489934.b, Department of Nephrology, , Baoji Central Hospital, ; No. 8 Jiangtan Road, Baoji, Shaanxi 721008 China
                [5 ]ISNI 0000 0004 1936 9916, GRID grid.412807.8, Department of Biomedical Informatics, , Vanderbilt University Medical Center, ; 1211 Medical Center Dr, Nashville, Tennessee 37232 USA
                [6 ]ISNI 0000 0001 2264 7217, GRID grid.152326.1, Department of Molecular Physiology and Biophysics, , Vanderbilt University, ; 1211 Medical Center Dr, Nashville, Tennessee 37232 USA
                [7 ]ISNI 0000000123704535, GRID grid.24516.34, Department of Nephrology, Shanghai East Hospital, , Tongji University School of Medicine, ; No. 150 Jimo Road, Shanghai, 200120 China
                [8 ]ISNI 0000 0004 1936 9094, GRID grid.40263.33, Department of Medicine, Rhode Island Hospital and Alpert Medical School, , Brown University, ; 593 Eddy St, Providence, Rhode Island 02903 USA
                [9 ]Department of Nephrology, Affiliated Hospital of Shaanxi Institute of Traditional Chinese Medicine, No. 2 Xihuamen, Xi’an, Shaanxi 710003 China
                [10 ]ISNI 0000 0001 0668 7243, GRID grid.266093.8, Division of Nephrology and Hypertension, School of Medicine, , University of California Irvine, ; 1001 Health Sciences Rd, Irvine, California 92897 USA
                [11 ]Department of Nephrology, Xi’an No. 4 Hospital, No. 21 Jiefang Road, Xi’an, 710004 China
                [12 ]ISNI 0000 0001 1431 9176, GRID grid.24695.3c, School of Chinese Materia Medica, , Beijing University of Chinese Medicine, ; No. 11 North Third Ring Road, Beijing, 100029 China
                Author information
                http://orcid.org/0000-0002-2259-7739
                http://orcid.org/0000-0002-0239-7342
                Article
                9329
                10.1038/s41467-019-09329-0
                6443780
                30931940
                d44203e1-4a98-46f7-bd00-d15378c50f18
                © The Author(s) 2019

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

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                : 13 April 2018
                : 6 March 2019
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