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Chen Q, Lu Q, Zhang L, Zhang C, Zhang J, Gu Y, Huang Q, Tang H. A novel endogenous retention-index for minimizing retention-time variations in metabolomic analysis with reversed-phase ultrahigh-performance liquid-chromatography and mass spectrometry. Talanta 2024; 268:125318. [PMID: 37875029 DOI: 10.1016/j.talanta.2023.125318] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 06/06/2023] [Revised: 10/07/2023] [Accepted: 10/14/2023] [Indexed: 10/26/2023]
Abstract
Consistent retention time (tR) of metabolites is vital for identification in metabolomic analysis with ultrahigh-performance liquid-chromatography (UPLC). To minimize inter-experimental tR variations from the reversed-phase UPLC-MS, we developed an endogenous retention-index (endoRI) using in-sample straight-chain acylcarnitines with different chain-length (LC, C0-C26) without additives. The endoRI-corrections reduced the tR variations caused by the combined changes of mobile phases, gradients, flow-rates, elution time, columns and temperature from up to 5.1 min-0.2 min for most metabolites in a model metabolome consisting of 91 metabolites and multiple biological matrices including human serum, plasma, fecal, urine, A549 cells and rabbit liver extracts. The endoRI-corrections also reduced the inter-batch and inter-platform tR variations from 1.5 min to 0.15 min for 95 % of detected features in the above biological samples. We further established a quantitative model between tR and LC for predicting tR values of acylcarnitines when absent in samples. This makes it possible to compare metabolites' tR from different tR databases and the UPLC-based metabolomic data from different batches.
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Affiliation(s)
- Qinsheng Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Qinwei Lu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Lianglong Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Chenhan Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Jingxian Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Yu Gu
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Qingxia Huang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China.
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Zhang J, Chen Q, Zhang L, Shi B, Yu M, Huang Q, Tang H. Simultaneously quantifying hundreds of acylcarnitines in multiple biological matrices within ten minutes using ultrahigh-performance liquid-chromatography and tandem mass spectrometry. J Pharm Anal 2024; 14:140-148. [PMID: 38352947 PMCID: PMC10859589 DOI: 10.1016/j.jpha.2023.10.004] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2023] [Revised: 09/28/2023] [Accepted: 10/14/2023] [Indexed: 02/16/2024] Open
Abstract
Acylcarnitines are metabolic intermediates of fatty acids and branched-chain amino acids having vital biofunctions and pathophysiological significances. Here, we developed a high-throughput method for quantifying hundreds of acylcarnitines in one run using ultrahigh performance liquid chromatography and tandem mass spectrometry (UPLC-MS/MS). This enabled simultaneous quantification of 1136 acylcarnitines (C0-C26) within 10-min with good sensitivity (limit of detection < 0.7 fmol), linearity (correlation coefficient > 0.992), accuracy (relative error < 20%), precision (coefficient of variation (CV), CV < 15%), stability (CV < 15%), and inter-technician consistency (CV < 20%, n = 6). We also established a quantitative structure-retention relationship (goodness of fit > 0.998) for predicting retention time (tR) of acylcarnitines with no standards and built a database of their multiple reaction monitoring parameters (tR, ion-pairs, and collision energy). Furthermore, we quantified 514 acylcarnitines in human plasma and urine, mouse kidney, liver, heart, lung, and muscle. This provides a rapid method for quantifying acylcarnitines in multiple biological matrices.
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Affiliation(s)
- Jingxian Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Qinsheng Chen
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Lianglong Zhang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Biru Shi
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Men Yu
- Wuhan Laboratory for Shanghai Metabolome Institute (SMI) Ltd., Wuhan, 430000, China
| | - Qingxia Huang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
| | - Huiru Tang
- State Key Laboratory of Genetic Engineering, School of Life Sciences, Human Phenome Institute, Zhangjiang Fudan International Innovation Center, Metabonomics and Systems Biology Laboratory at Shanghai International Centre for Molecular Phenomics, Zhongshan Hospital, Fudan University, Shanghai, 200032, China
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3
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Bittremieux W, Avalon NE, Thomas SP, Kakhkhorov SA, Aksenov AA, Gomes PWP, Aceves CM, Caraballo-Rodríguez AM, Gauglitz JM, Gerwick WH, Huan T, Jarmusch AK, Kaddurah-Daouk RF, Kang KB, Kim HW, Kondić T, Mannochio-Russo H, Meehan MJ, Melnik AV, Nothias LF, O'Donovan C, Panitchpakdi M, Petras D, Schmid R, Schymanski EL, van der Hooft JJJ, Weldon KC, Yang H, Xing S, Zemlin J, Wang M, Dorrestein PC. Open access repository-scale propagated nearest neighbor suspect spectral library for untargeted metabolomics. Nat Commun 2023; 14:8488. [PMID: 38123557 PMCID: PMC10733301 DOI: 10.1038/s41467-023-44035-y] [Citation(s) in RCA: 8] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/05/2023] [Accepted: 11/28/2023] [Indexed: 12/23/2023] Open
Abstract
Despite the increasing availability of tandem mass spectrometry (MS/MS) community spectral libraries for untargeted metabolomics over the past decade, the majority of acquired MS/MS spectra remain uninterpreted. To further aid in interpreting unannotated spectra, we created a nearest neighbor suspect spectral library, consisting of 87,916 annotated MS/MS spectra derived from hundreds of millions of MS/MS spectra originating from published untargeted metabolomics experiments. Entries in this library, or "suspects," were derived from unannotated spectra that could be linked in a molecular network to an annotated spectrum. Annotations were propagated to unknowns based on structural relationships to reference molecules using MS/MS-based spectrum alignment. We demonstrate the broad relevance of the nearest neighbor suspect spectral library through representative examples of propagation-based annotation of acylcarnitines, bacterial and plant natural products, and drug metabolism. Our results also highlight how the library can help to better understand an Alzheimer's brain phenotype. The nearest neighbor suspect spectral library is openly available for download or for data analysis through the GNPS platform to help investigators hypothesize candidate structures for unknown MS/MS spectra in untargeted metabolomics data.
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Affiliation(s)
- Wout Bittremieux
- Department of Computer Science, University of Antwerp, 2020, Antwerpen, Belgium.
| | - Nicole E Avalon
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, 92093, USA
| | - Sydney P Thomas
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Sarvar A Kakhkhorov
- Laboratory of Physical and Chemical Methods of Research, Center for Advanced Technologies, Tashkent, 100174, Uzbekistan
- Department of Food Science, Faculty of Science, University of Copenhagen, Rolighedsvej 26, 1958, Frederiksberg C, Denmark
| | - Alexander A Aksenov
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Chemistry, University of Connecticut, Storrs, CT, 06269, USA
- Arome Science inc., Farmington, CT, 06032, USA
| | - Paulo Wender P Gomes
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Christine M Aceves
- Department of Immunology and Microbiology, The Scripps Research Institute, La Jolla, CA, 92037, USA
| | - Andrés Mauricio Caraballo-Rodríguez
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Julia M Gauglitz
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - William H Gerwick
- Scripps Institution of Oceanography, University of California San Diego, La Jolla, CA, 92093, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
| | - Tao Huan
- Department of Chemistry, University of British Columbia, Vancouver, BC, V6T 1Z1, Canada
| | - Alan K Jarmusch
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
- Immunity, Inflammation, and Disease Laboratory, Division of Intramural Research, National Institute of Environmental Health Sciences, National Institutes of Health, Research Triangle Park, Durham, NC, 27709, USA
| | - Rima F Kaddurah-Daouk
- Department of Psychiatry and Behavioral Sciences, Duke University School of Medicine, Durham, NC, 27701, USA
- Department of Medicine, Duke University, Durham, NC, 27710, USA
- Duke Institute of Brain Sciences, Duke University, Durham, NC, 27710, USA
| | - Kyo Bin Kang
- College of Pharmacy and Research Institute of Pharmaceutical Sciences, Sookmyung Women's University, Seoul, 04310, Korea
| | - Hyun Woo Kim
- College of Pharmacy and Integrated Research Institute for Drug Development, Dongguk University, Goyang, 10326, Korea
| | - Todor Kondić
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4367, Belvaux, Luxembourg
| | - Helena Mannochio-Russo
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Biochemistry and Organic Chemistry, Institute of Chemistry, São Paulo State University, Araraquara, 14800-901, Brazil
| | - Michael J Meehan
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Alexey V Melnik
- Department of Chemistry, University of Connecticut, Storrs, CT, 06269, USA
- Arome Science inc., Farmington, CT, 06032, USA
| | - Louis-Felix Nothias
- Université Côte d'Azur, CNRS, ICN, Nice, France
- Interdisciplinary Institute for Artificial Intelligence (3iA) Côte d'Azur, Nice, France
| | - Claire O'Donovan
- European Molecular Biology Laboratory, European Bioinformatics Institute (EMBL-EBI), Wellcome Genome Campus, Hinxton, Cambridge, CB10 1SD, UK
| | - Morgan Panitchpakdi
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Daniel Petras
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
- Interfaculty Institute of Microbiology and Infection Medicine, University of Tuebingen, 72076, Tuebingen, Germany
- Department of Biochemistry, University of California Riverside, Riverside, CA, 92507, USA
| | - Robin Schmid
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Emma L Schymanski
- Luxembourg Centre for Systems Biomedicine, University of Luxembourg, L-4367, Belvaux, Luxembourg
| | - Justin J J van der Hooft
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
- Bioinformatics Group, Wageningen University & Research, 6708 PB, Wageningen, The Netherlands
| | - Kelly C Weldon
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Heejung Yang
- Laboratory of Natural Products Chemistry, College of Pharmacy, Kangwon National University, Chuncheon, 24341, Korea
| | - Shipei Xing
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
- Department of Chemistry, University of British Columbia, Vancouver, BC, V6T 1Z1, Canada
| | - Jasmine Zemlin
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
| | - Mingxun Wang
- Department of Computer Science and Engineering, University of California Riverside, Riverside, CA, 92507, USA
| | - Pieter C Dorrestein
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA.
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA.
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Liu Z, Ulrich vonBargen R, Kendricks AL, Wheeler K, Leão AC, Sankaranarayanan K, Dean DA, Kane SS, Hossain E, Pollet J, Bottazzi ME, Hotez PJ, Jones KM, McCall LI. Localized cardiac small molecule trajectories and persistent chemical sequelae in experimental Chagas disease. Nat Commun 2023; 14:6769. [PMID: 37880260 PMCID: PMC10600178 DOI: 10.1038/s41467-023-42247-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/19/2023] [Accepted: 10/04/2023] [Indexed: 10/27/2023] Open
Abstract
Post-infectious conditions present major health burdens but remain poorly understood. In Chagas disease (CD), caused by Trypanosoma cruzi parasites, antiparasitic agents that successfully clear T. cruzi do not always improve clinical outcomes. In this study, we reveal differential small molecule trajectories between cardiac regions during chronic T. cruzi infection, matching with characteristic CD apical aneurysm sites. Incomplete, region-specific, cardiac small molecule restoration is observed in animals treated with the antiparasitic benznidazole. In contrast, superior restoration of the cardiac small molecule profile is observed for a combination treatment of reduced-dose benznidazole plus an immunotherapy, even with less parasite burden reduction. Overall, these results reveal molecular mechanisms of CD treatment based on simultaneous effects on the pathogen and on host small molecule responses, and expand our understanding of clinical treatment failure in CD. This link between infection and subsequent persistent small molecule perturbation broadens our understanding of infectious disease sequelae.
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Affiliation(s)
- Zongyuan Liu
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA
| | - Rebecca Ulrich vonBargen
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA
- Department of Biomedical Engineering, University of Oklahoma, Norman, OK, USA
| | | | - Kate Wheeler
- Department of Biology, University of Oklahoma, Norman, OK, USA
| | - Ana Carolina Leão
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Krithivasan Sankaranarayanan
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA
| | - Danya A Dean
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA
| | - Shelley S Kane
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA
| | - Ekram Hossain
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA
| | - Jeroen Pollet
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
| | - Maria Elena Bottazzi
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Peter J Hotez
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA
| | - Kathryn M Jones
- Department of Pediatrics, Baylor College of Medicine, Houston, TX, USA.
- Department of Molecular Virology and Microbiology, Baylor College of Medicine, Houston, TX, USA.
| | - Laura-Isobel McCall
- Department of Chemistry and Biochemistry, University of Oklahoma, Norman, OK, USA.
- Laboratories of Molecular Anthropology and Microbiome Research, University of Oklahoma, Norman, OK, USA.
- Department of Microbiology and Plant Biology, University of Oklahoma, Norman, OK, USA.
- Department of Chemistry and Biochemistry, San Diego State University, San Diego, CA, USA.
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Yu Q, Liu X, Keller MP, Navarrete-Perea J, Zhang T, Fu S, Vaites LP, Shuken SR, Schmid E, Keele GR, Li J, Huttlin EL, Rashan EH, Simcox J, Churchill GA, Schweppe DK, Attie AD, Paulo JA, Gygi SP. Sample multiplexing-based targeted pathway proteomics with real-time analytics reveals the impact of genetic variation on protein expression. Nat Commun 2023; 14:555. [PMID: 36732331 PMCID: PMC9894840 DOI: 10.1038/s41467-023-36269-7] [Citation(s) in RCA: 13] [Impact Index Per Article: 13.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/12/2022] [Accepted: 01/20/2023] [Indexed: 02/04/2023] Open
Abstract
Targeted proteomics enables hypothesis-driven research by measuring the cellular expression of protein cohorts related by function, disease, or class after perturbation. Here, we present a pathway-centric approach and an assay builder resource for targeting entire pathways of up to 200 proteins selected from >10,000 expressed proteins to directly measure their abundances, exploiting sample multiplexing to increase throughput by 16-fold. The strategy, termed GoDig, requires only a single-shot LC-MS analysis, ~1 µg combined peptide material, a list of up to 200 proteins, and real-time analytics to trigger simultaneous quantification of up to 16 samples for hundreds of analytes. We apply GoDig to quantify the impact of genetic variation on protein expression in mice fed a high-fat diet. We create several GoDig assays to quantify the expression of multiple protein families (kinases, lipid metabolism- and lipid droplet-associated proteins) across 480 fully-genotyped Diversity Outbred mice, revealing protein quantitative trait loci and establishing potential linkages between specific proteins and lipid homeostasis.
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Affiliation(s)
- Qing Yu
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Xinyue Liu
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Mark P Keller
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | | | - Tian Zhang
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Sipei Fu
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Laura P Vaites
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Steven R Shuken
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Ernst Schmid
- Department of Biological Chemistry and Molecular Pharmacology, Harvard Medical School, Boston, MA, 02115, USA
| | | | - Jiaming Li
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Edward L Huttlin
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Edrees H Rashan
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Judith Simcox
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | | | - Devin K Schweppe
- Department of Genome Sciences, University of Washington, Seattle, WA, 98105, USA
| | - Alan D Attie
- Department of Biochemistry, University of Wisconsin-Madison, Madison, WI, 53706, USA
| | - Joao A Paulo
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA
| | - Steven P Gygi
- Department of Cell Biology, Harvard Medical School, Boston, MA, 02115, USA.
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6
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da Silva KM, van de Lavoir M, Robeyns R, Iturrospe E, Verheggen L, Covaci A, van Nuijs ALN. Guidelines and considerations for building multidimensional libraries for untargeted MS-based metabolomics. Metabolomics 2022; 19:4. [PMID: 36576608 DOI: 10.1007/s11306-022-01965-w] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/10/2022] [Accepted: 12/05/2022] [Indexed: 12/29/2022]
Abstract
INTRODUCTION Feature annotation is crucial in untargeted metabolomics but remains a major challenge. The large pool of metabolites collected under various instrumental conditions is underrepresented in publicly available databases. Retention time (RT) and collision cross section (CCS) measurements from liquid chromatography ion mobility high-resolution mass spectrometers can be employed in addition to MS/MS spectra to improve the confidence of metabolite annotation. Recent advancements in machine learning focus on improving the accuracy of predictions for CCS and RT values. Therefore, high-quality experimental data are crucial to be used either as training datasets or as a reference for high-confidence matching. METHODS This manuscript provides an easy-to-use workflow for the creation of an in-house metabolite library, offers an overview of alternative solutions, and discusses the challenges and advantages of using open-source software. A total of 100 metabolite standards from various classes were analyzed and subjected to the described workflow for library generation. RESULTS AND DISCUSSION The outcome was an open-access available NIST format metabolite library (.msp) with multidimensional information. The library was used to evaluate CCS prediction tools, MS/MS spectra heterogeneities (e.g., multiple adducts, in-source fragmentation, radical fragment ions using collision-induced dissociation), and the reporting of RT.
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Affiliation(s)
- Katyeny Manuela da Silva
- Department of Pharmaceutical Sciences, Faculty of Pharmaceutical, Toxicological Centre, Biomedical and Veterinary Sciences, Campus Drie Eiken, University of Antwerp, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Maria van de Lavoir
- Department of Pharmaceutical Sciences, Faculty of Pharmaceutical, Toxicological Centre, Biomedical and Veterinary Sciences, Campus Drie Eiken, University of Antwerp, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Rani Robeyns
- Department of Pharmaceutical Sciences, Faculty of Pharmaceutical, Toxicological Centre, Biomedical and Veterinary Sciences, Campus Drie Eiken, University of Antwerp, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Elias Iturrospe
- Department of Pharmaceutical Sciences, Faculty of Pharmaceutical, Toxicological Centre, Biomedical and Veterinary Sciences, Campus Drie Eiken, University of Antwerp, Universiteitsplein 1, 2610, Antwerp, Belgium
- Department of In Vitro Toxicology and Dermato-Cosmetology, Faculty of Medicine and Pharmacy, Campus Jette, Vrije Universiteit Brussel, Laarbeeklaan 103, 1090, Brussels, Belgium
| | - Lisa Verheggen
- Department of Pharmaceutical Sciences, Faculty of Pharmaceutical, Toxicological Centre, Biomedical and Veterinary Sciences, Campus Drie Eiken, University of Antwerp, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Adrian Covaci
- Department of Pharmaceutical Sciences, Faculty of Pharmaceutical, Toxicological Centre, Biomedical and Veterinary Sciences, Campus Drie Eiken, University of Antwerp, Universiteitsplein 1, 2610, Antwerp, Belgium
| | - Alexander L N van Nuijs
- Department of Pharmaceutical Sciences, Faculty of Pharmaceutical, Toxicological Centre, Biomedical and Veterinary Sciences, Campus Drie Eiken, University of Antwerp, Universiteitsplein 1, 2610, Antwerp, Belgium.
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7
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Bittremieux W, Wang M, Dorrestein PC. The critical role that spectral libraries play in capturing the metabolomics community knowledge. Metabolomics 2022; 18:94. [PMID: 36409434 DOI: 10.1007/s11306-022-01947-y] [Citation(s) in RCA: 24] [Impact Index Per Article: 12.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 08/01/2022] [Accepted: 10/19/2022] [Indexed: 11/22/2022]
Abstract
BACKGROUND Spectral library searching is currently the most common approach for compound annotation in untargeted metabolomics. Spectral libraries applicable to liquid chromatography mass spectrometry have grown in size over the past decade to include hundreds of thousands to millions of mass spectra and tens of thousands of compounds, forming an essential knowledge base for the interpretation of metabolomics experiments. AIM OF REVIEW We describe existing spectral library resources, highlight different strategies for compiling spectral libraries, and discuss quality considerations that should be taken into account when interpreting spectral library searching results. Finally, we describe how spectral libraries are empowering the next generation of machine learning tools in computational metabolomics, and discuss several opportunities for using increasingly accessible large spectral libraries. KEY SCIENTIFIC CONCEPTS OF REVIEW This review focuses on the current state of spectral libraries for untargeted LC-MS/MS based metabolomics. We show how the number of entries in publicly accessible spectral libraries has increased more than 60-fold in the past eight years to aid molecular interpretation and we discuss how the role of spectral libraries in untargeted metabolomics will evolve in the near future.
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Affiliation(s)
- Wout Bittremieux
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA
| | - Mingxun Wang
- Department of Computer Science, University of California Riverside, Riverside, CA, 92507, USA
| | - Pieter C Dorrestein
- Collaborative Mass Spectrometry Innovation Center, University of California San Diego, La Jolla, CA, 92093, USA.
- Skaggs School of Pharmacy and Pharmaceutical Sciences, University of California San Diego, La Jolla, CA, 92093, USA.
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8
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Long time stability of 35 small endogenous biomolecules in dried urine spotted on various surfaces and environmental conditions. Forensic Sci Int 2022; 339:111420. [PMID: 35985138 DOI: 10.1016/j.forsciint.2022.111420] [Citation(s) in RCA: 2] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/05/2022] [Revised: 08/04/2022] [Accepted: 08/09/2022] [Indexed: 11/23/2022]
Abstract
Analysis of endogenous biomolecules is an important aspect of many forensic investigations especially with focus on DNA analysis for perpetrator/victim identification and protein analysis for body fluid identification. Recently, small endogenous biomolecules have been used for differentiation of synthetic "fake" urine from authentic urine and might be also useful for biofluid identification. Therefore, the aim of this study was to adapt and optimize a method for analysis of small EBs and to investigate long time stability of 35 small endogenous biomolecules (including acylcarnitines with their isomers and metabolites as well as amino acids with their metabolites) in spotted urine samples. Urine samples were spotted on seven different surfaces (Whatman 903 Protein Saver Cards, cotton swabs, cotton glove, denim, underwear, and smooth and rough flagstone) and stored under six environmental conditions (reference condition, sunlight, LED light, 4 °C, 37 °C, humidity of 95%). At certain time points (d0, d7, d28 and d56) samples were analyzed in triplicates by an optimized extraction and LC-HRMS approach. In addition, the urine marker Tamm-Horsfall-Protein was determined on cotton swabs at the same time points using a commercial lateral flow test. Twenty-one of 35 small endogenous biomolecules were stable on most materials/surfaces and under most storage conditions. Significant lower endogenous biomolecule peak areas were found for rough flagstone and underwear as well as for high humidity storage. Kynurenic acid proved to be photo labile. While high long time stabilities were found for 19 of 28 acylcarnitines, nine acylcarnitines showed aberrant stability patterns without evident structural reason. For Tamm-Horsfall-Protein degradation within 28 days was observed even under reference conditions. The presented study demonstrated the value of sensitive LC-HRMS analysis for small endogenous biomolecules / pattern. However, further studies will be indispensable for unambiguous body fluid identification by small endogenous biomolecules.
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9
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Dambrova M, Makrecka-Kuka M, Kuka J, Vilskersts R, Nordberg D, Attwood MM, Smesny S, Sen ZD, Guo AC, Oler E, Tian S, Zheng J, Wishart DS, Liepinsh E, Schiöth HB. Acylcarnitines: Nomenclature, Biomarkers, Therapeutic Potential, Drug Targets, and Clinical Trials. Pharmacol Rev 2022; 74:506-551. [PMID: 35710135 DOI: 10.1124/pharmrev.121.000408] [Citation(s) in RCA: 134] [Impact Index Per Article: 67.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/16/2022] Open
Abstract
Acylcarnitines are fatty acid metabolites that play important roles in many cellular energy metabolism pathways. They have historically been used as important diagnostic markers for inborn errors of fatty acid oxidation and are being intensively studied as markers of energy metabolism, deficits in mitochondrial and peroxisomal β -oxidation activity, insulin resistance, and physical activity. Acylcarnitines are increasingly being identified as important indicators in metabolic studies of many diseases, including metabolic disorders, cardiovascular diseases, diabetes, depression, neurologic disorders, and certain cancers. The US Food and Drug Administration-approved drug L-carnitine, along with short-chain acylcarnitines (acetylcarnitine and propionylcarnitine), is now widely used as a dietary supplement. In light of their growing importance, we have undertaken an extensive review of acylcarnitines and provided a detailed description of their identity, nomenclature, classification, biochemistry, pathophysiology, supplementary use, potential drug targets, and clinical trials. We also summarize these updates in the Human Metabolome Database, which now includes information on the structures, chemical formulae, chemical/spectral properties, descriptions, and pathways for 1240 acylcarnitines. This work lays a solid foundation for identifying, characterizing, and understanding acylcarnitines in human biosamples. We also discuss the emerging opportunities for using acylcarnitines as biomarkers and as dietary interventions or supplements for many wide-ranging indications. The opportunity to identify new drug targets involved in controlling acylcarnitine levels is also discussed. SIGNIFICANCE STATEMENT: This review provides a comprehensive overview of acylcarnitines, including their nomenclature, structure and biochemistry, and use as disease biomarkers and pharmaceutical agents. We present updated information contained in the Human Metabolome Database website as well as substantial mapping of the known biochemical pathways associated with acylcarnitines, thereby providing a strong foundation for further clarification of their physiological roles.
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Affiliation(s)
- Maija Dambrova
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Marina Makrecka-Kuka
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Janis Kuka
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Reinis Vilskersts
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Didi Nordberg
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Misty M Attwood
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Stefan Smesny
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Zumrut Duygu Sen
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - An Chi Guo
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Eponine Oler
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Siyang Tian
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Jiamin Zheng
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - David S Wishart
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Edgars Liepinsh
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
| | - Helgi B Schiöth
- Laboratory of Pharmaceutical Pharmacology, Latvian Institute of Organic Synthesis, Riga, Latvia (M.D., M.M.-K., J.K., R.V., E.L.); Section of Functional Pharmacology, Department of Neuroscience, Uppsala University, Uppsala, Sweden, (D.N., M.M.A., H.B.S.); Department of Psychiatry, Jena University Hospital, Jena, Germany (S.S., Z.D.S.); and Department of Biological Sciences, University of Alberta, Edmonton, Canada (A.C.G., E.O., S.T., J.Z., D.S.W.)
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10
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Liu HX, Liu QJ. Logistic role of carnitine shuttle system on radiation-induced L-carnitine and acylcarnitines alteration. Int J Radiat Biol 2022; 98:1-14. [PMID: 35384773 DOI: 10.1080/09553002.2022.2063430] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/02/2021] [Revised: 03/17/2022] [Accepted: 03/18/2022] [Indexed: 12/13/2022]
Abstract
PURPOSE With the development of radiation metabolomics, a large number of radiation-related metabolic biomarkers have been identified and validated. The L-carnitine and acylcarnitines have the potential to be the new promising candidate indicators of radiation exposure. This review summarizes the effect of carnitine shuttle system on the profile of acylcarnitines and correlates the radiation effects on upstream regulators of carnitine shuttle system with the change characteristics of L-carnitine and acylcarnitines after irradiation across different animal models as well as a few humans. CONCLUSIONS Studies report that acylcarnitines were ubiquitously elevated after irradiation, especially the free L-carnitine and short-chain acylcarnitines (C2-C5). However, the molecular mechanism underlying acylcarnitine alterations after irradiation is not fully investigated, and further studies are needed to explore the biological effect and its mechanism. The activity of the carnitine shuttle system plays a key role in the alteration of L-carnitine and acylcarnitines, and the upstream regulators of the system are known to be affected by irradiation. These evidences indicate that that there is a logistic role of carnitine shuttle system on radiation-induced L-carnitine and acylcarnitines alteration.
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Affiliation(s)
- Hai-Xiang Liu
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
| | - Qing-Jie Liu
- China CDC Key Laboratory of Radiological Protection and Nuclear Emergency, National Institute for Radiological Protection, Chinese Center for Disease Control and Prevention, Beijing, People's Republic of China
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11
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Pannkuk EL, Laiakis EC, Angdisen J, Jayatilake MM, Ake P, Lin LYT, Li HH, Fornace AJ. Small Molecule Signatures of Mice Lacking T-cell p38 Alternate Activation, a Model for Immunosuppression Conditions, after Total-Body Irradiation. Radiat Res 2022; 197:613-625. [PMID: 35245386 DOI: 10.1667/rade-21-00199.1] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 10/05/2021] [Accepted: 01/24/2022] [Indexed: 11/03/2022]
Abstract
Several diagnostic biodosimetry tools have been in development that may aid in radiological/nuclear emergency responses. Of these, correlating changes in non-invasive biofluid small-molecule signatures to tissue damage from ionizing radiation exposure show promise for inclusion in predictive biodosimetry models. Integral to dose reconstruction has been determining how genotypic variation in the general population will affect model performance. Here, we used a mouse model that lacks the T-cell receptor specific alternative p38 pathway [p38αβY323F, double knock-in (DKI) mice] to determine how attenuated autoimmune and inflammatory responses may affect dose reconstruction. We exposed adult male DKI mice (8-10 weeks old) to 2 and 7 Gy in parallel with wild-type mice and assessed perturbations in urine (days 1, 3, 7) and serum (day 1) using a global metabolomics approach. A multidimensional scaling plot showed excellent separation of radiation-exposed groups in wild-type mice with slightly dampened responses in DKI mice. Validated metabolite panels were developed for urine [N6,N6,N6-trimethyllysine (TML), N1-acetylspermidine, spermidine, carnitine, acylcarnitine C21H35NO5, 4-aminohippuric acid] and serum [phenylalanine, glutamine, propionylcarnitine, lysophosphatidylcholine (LysoPC 14:0), LysoPC (22:5)] to determine the area under the receiver operating characteristic curve (AUROC). For both urine and serum, excellent sensitivity and specificity (AUROC > 0.90) was observed for 0 Gy vs. 7 Gy groups irrespective of genotype using identical metabolite panels. Similarly, excellent to fair classification (AUROC > 0.75) was observed for ≤2 Gy vs. 7 Gy mice for both genotypes, however, model performance declined (AUROC < 0.75) between genotypes after irradiation. Overall, these results suggest immunosuppression should not compromise small molecule multiplex panels used in dose reconstruction for biodosimetry.
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Affiliation(s)
- Evan L Pannkuk
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.,Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC
| | - Evagelia C Laiakis
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.,Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC
| | - Jerry Angdisen
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC
| | - Meth M Jayatilake
- Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC
| | - Pelagie Ake
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC
| | - Lorreta Yun-Tien Lin
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC
| | - Heng-Hong Li
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.,Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC
| | - Albert J Fornace
- Department of Oncology, Lombardi Comprehensive Cancer Center, Georgetown University Medical Center, Washington, DC.,Department of Biochemistry and Molecular & Cellular Biology, Georgetown University Medical Center, Washington, DC
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12
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Villaseñor A, Godzien J, Barker-Tejeda TC, Gonzalez-Riano C, López-López Á, Dudzik D, Gradillas A, Barbas C. Analytical approaches for studying oxygenated lipids in the search of potential biomarkers by LC-MS. Trends Analyt Chem 2021. [DOI: 10.1016/j.trac.2021.116367] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/12/2022]
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13
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Dong Q, Yan X, Liang Y, Markey SP, Sheetlin SL, Remoroza CA, Wallace WE, Stein SE. Comprehensive Analysis of Tryptic Peptides Arising from Disulfide Linkages in NISTmAb and Their Use for Developing a Mass Spectral Library. J Proteome Res 2021; 20:1612-1629. [PMID: 33555887 PMCID: PMC9278810 DOI: 10.1021/acs.jproteome.0c00823] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 12/28/2022]
Abstract
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This
work presents methods for identifying and then creating a
mass spectral library for disulfide-linked peptides originating from
the NISTmAb, a reference material of the humanized IgG1k monoclonal
antibody (RM 8671). Analyses involved both partially reduced and non-reduced
samples under neutral and weakly basic conditions followed by nanoflow
liquid chromatography tandem mass spectrometry (LC–MS/MS).
Spectra of peptides containing disulfide bonds are identified by both
MS1 ion and MS2 fragment ion data in order to completely map all the
disulfide linkages in the NISTmAb. This led to the detection of 383
distinct disulfide-linked peptide ions, arising from fully tryptic
cleavage, missed cleavage, irregular cleavage, complex Met/Trp oxidation
mixtures, and metal adducts. Fragmentation features of disulfide bonds
under low-energy collision dissociation were examined. These include
(1) peptide bond cleavage leaving disulfide bonds intact; (2) disulfide
bond cleavage, often leading to extensive fragmentation; and (3) double
cleavage products resulting from breakages of two peptide bonds or
both peptide and disulfide bonds. Automated annotation of various
complex MS/MS fragments enabled the identification of disulfide-linked
peptides with high confidence. Peptides containing each of the nine
native disulfide bonds were identified along with 86 additional disulfide
linkages arising from disulfide bond shuffling. The presence of shuffled
disulfides was nearly completely abrogated by refining digest conditions.
A curated spectral library of 702 disulfide-linked peptide spectra
was created from this analysis and is publicly available for free
download. Since all IgG1 antibodies have the same constant regions,
the resulting library can be used as a tool for facile identification
of “hard-to-find” disulfide-bonded peptides. Moreover,
we show that one may identify such peptides originating from IgG1
proteins in human serum, thereby serving as a means of monitoring
the completeness of protein reduction in proteomics studies. Data
are available via ProteomeXchange with identifier PXD023358.
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Affiliation(s)
- Qian Dong
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
| | - Xinjian Yan
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
| | - Yuxue Liang
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
| | - Sanford P Markey
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
| | - Sergey L Sheetlin
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
| | - Concepcion A Remoroza
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
| | - William E Wallace
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
| | - Stephen E Stein
- Biomolecular Measurement Division, National Institute of Standards and Technology, 100 Bureau Drive, Stop 8362, Gaithersburg, Maryland 20899, United States
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