首页 > 分享 > 代谢组学在毒理学研究中的应用

代谢组学在毒理学研究中的应用

花匠小妙招
2025-05-15 17:10

摘要:

代谢组学是继基因组学、转录组学及蛋白质组学之后发展起来的一门新兴组学，是整合包括色谱-质谱（MS）和/或核磁共振（NMR）等现代分析技术、生物化学以及生物信息学等学科的一门交叉学科技术，用于研究生命活动链条下游的代谢物内稳态情况。代谢组学作为传统毒理学毒性研究技术的有效补充，以人体、实验动物和细胞等为对象，通过分析生物流体、细胞和组织样品受内、外因素干预后代谢物种类及数量的变化，进行快速准确的早期毒性筛选以及后期毒性机理研究和毒性生物标志物的发现。本文拟从代谢组学的技术发展以及其在毒理学中的应用进展和存在的问题等方面进行综述性回顾。关键词: 代谢组学 / 毒理学 / 代谢通路 / 质谱 / 核磁共振

Abstract: Metabolomics has been labeled one of the new "omics", joining genomics, transcriptomics, and proteomics as an interdisciplinary science integrating many advanced analytical technologies including chromatography-mass spectrometry (MS) and/or nuclear magnetic resonance (NMR), biochemistry, and bioinformatics. Metabolomics, as a tool of understanding global systems biology, has been employed to investigate the homeostasis of downstream metabolites generated by biological activities. Metabolomics is an emerging alternative and complementary technology in toxicology study as it has been widely used to rapidly diagnose early toxicity, explore subsequent toxic mechanism, and identify corresponding biomarkers by profiling metabolite changes induced by toxins and/or toxicants in biofluids, cells, and tissues. This article reviewed and discussed the current technical development of metabolomics, and its applications and challenges in toxicology.

[1]

UPPAL K, WALKER D I, LIU K, et al. Computational Metabolomics:a Framework for the Million Metabolome[J]. Chem Res Toxicol, 2016, 29(12):1956-1975.

doi: 10.1021/acs.chemrestox.6b00179 [2]

BOUHIFD M, HARTUNG T, HOGBERG H T, et al. Review:toxicometabolomics[J]. J Appl Toxicol, 2013, 33(12):1365-1383.

doi: 10.1002/jat.v33.12 [3]

HEIJNE W H, KIENHUIS AS, VAN OMMEN B, et al. Systems toxicology:applications of toxicogenomics, transcriptomics, proteomics and metabolomics in toxicology[J]. Expert Rev Proteom, 2005, 2(5):767-780.

doi: 10.1586/14789450.2.5.767 [4]

JOHNSON C H, PATTERSON A D, IDLE J R, et al. Xenobiotic metabolomics:major impact on the metabolome[J]. Annu Rev Pharmacol Toxicol, 2012, 52:37-56.

doi: 10.1146/annurev-pharmtox-010611-134748 [5]

RAMIREZ T, DANESHIAN M, KAMP H, et al. Metabolomics in toxicology and preclinical research[J]. Altex, 2013, 30(2):209-225.

doi: 10.14573/altex [6]

SUMNER L W, AMBERG A, BARRETT D, et al. Proposed minimum reporting standards for chemical analysis:chemical analysis working group(CAWG)metabolomics standards initiative(MSI)[J]. Metabolomics, 2007, 3(3):211-221.

doi: 10.1007/s11306-007-0082-2 [7]

ABRANTES A M, RIO J, TAVARES L C, et al. Magnetic resonance spectroscopy in cancer diagnostics[J]. Oncol Rev, 2010, 4(3):177-184.

doi: 10.1007/s12156-010-0050-3 [8]

ROUX A, LISON D, JUNOT C, et al. Applications of liquid chromatography coupled to mass spectrometry-based metabolomics in clinical chemistry and toxicology:a review[J]. Clin Biochem, 2011, 44(1):119-135.

doi: 10.1016/j.clinbiochem.2010.08.016 [9]

MOCO S, VERVOORT J, MOCO S, et al. Metabolomics technologies and metabolite identification[J]. TrAC Trends Analyt Chem, 2007, 26(9):855-866.

doi: 10.1016/j.trac.2007.08.003 [10]

ZHAO Y H, YUAN S J, CHEN H, et al. Application of LCMS-based metabolomics in the evaluation of renal toxicity and identification of biomarker[J]. Chin J Pharmaceut Anal, 2015, 35(10):1691-1696.

[11]

TANG DQ, ZOU L, YIN XX, et al. HILIC-MS for metabolomics:an attractive and complementary approach to RPLC-MS[J]. Mass Spectrom Rev, 2016, 35(5):574-600.

doi: 10.1002/mas.v35.5 [12]

BOUATRA S, AZIAT F, MANDAL R, et al. The human urine metabolome[J]. PLoS One, 2013, 8(9):e73076.

doi: 10.1371/journal.pone.0073076 [13]

RAMAUTAR R, SOMSEN G W, DE JONG G J. CE-MS for metabolomics:developments and applications in the period 2014-2016[J]. Electrophoresis, 2017, 38(1):190-202.

doi: 10.1002/elps.201600370 [14]

LABOUREUR L, OLLERO M, TOUBOUL D. Lipidomics by supercritical fluid chromatography[J]. Int J Mol Sci, 2015, 16(6):13868-13884.

[15]

WOLFER A M, LOZANO S, UMBDENSTOCK T, et al. UPLC-MS retention time prediction:a machine learning approach to metabolite identification in untargeted profiling[J]. Metabolomics, 2016, 12(1):8.

doi: 10.1007/s11306-015-0888-2 [16]

SPALDING J L, CHO K, MAHIEU N G, et al. Bar coding MS2 spectra for metabolite identification[J]. Anal Chem, 2016, 88(5):2538-2542.

doi: 10.1021/acs.analchem.5b04925 [17]

RATHAHAO-PARIS E, ALVES S, JUNOT C, et al. High resolution mass spectrometry for structural identification of metabolites in metabolomics[J]. Metabolomics, 2016, 12(1):10.

doi: 10.1007/s11306-015-0882-8 [18]

DIAS D A, JONES O A, BEALE D J, et al. Current and future perspectives on the structural identification of small molecules in biological systems[J]. Metabolites, 2016, 6(4):46.

doi: 10.3390/metabo6040046 [19]

PSYCHOGIOS N, HAU D D, PENG J, et al. The human serum metabolome[J]. PLoS One, 2011, 6(2):e16957.

doi: 10.1371/journal.pone.0016957 [20]

HUAN T, TANG C, LI R, et al. MyCompoundID MS/MS search:metabolite identification using a library of predicted fragment-ion-spectra of 383, 830 possible human metabolites[J]. Anal Chem, 2015, 87(20):10619-10626.

doi: 10.1021/acs.analchem.5b03126 [21]

BARNES S, BENTON H P, CASAZZA K, et al. Training in metabolomics research. Ⅱ. Processing and statistical analysis of metabolomics data, metabolite identification, pathway analysis, applications of metabolomics and its future[J]. J Mass Spectrom, 2016, 51(8):535-548.

doi: 10.1002/jms.3780 [22]

SHAHAF N, ROGACHEV I, HEINIG U, et al. The WEIZMASS spectral library for high-confidence metabolite identification[J]. Nat Commun, 2016, 7:12423.

doi: 10.1038/ncomms12423 [23]

VINAIXA M, SCHYMANSKI E L, NEUMANN S, et al. Mass spectral databases for LC/MS-and GC/MS-based metabolomics:state of the field and future prospects[J]. TrAC Trends Anal Chem, 2016, 78:23-35.

doi: 10.1016/j.trac.2015.09.005 [24]

STANSTRUP J, NEUMANN S, VRHOVSEK U. PredRet:prediction of retention time by direct mapping between multiple chromatographic systems[J]. Anal Chem, 2015, 87(18):9421-9428.

doi: 10.1021/acs.analchem.5b02287 [25]

QUILLIAM M A. Retention index standards for liquid chromatography, US, 20150140593A1[P]. 2013-03-15.

[26]

PRZYBYLOWSKI P, WASILEWSKI G, KOC-ZORAWSKA E, et al. Metabolomics analysis in assessing immunosuppressive drug toxicity:abstract# C1604[J]. Am J Transplant, 2014, 14:431.

[27]

FENG J J, HAO G, MIN C Y, et al. Metabonomics of liver toxicity from Traditional Chinese Medicine Huang-Yao-Zi studied by mass spectrum-based orthogonal projection method[J]. Chemometr Intell Lab Syst, 2014, 135:201-207.

doi: 10.1016/j.chemolab.2014.04.016 [28]

ZHAO Y Y, LIN R C. Metabolomics in nephrotoxicity[J]. Adv Clin Chem, 2014, 65:69-89.

doi: 10.1016/B978-0-12-800141-7.00003-6 [29]

RAMIREZ T, BORDAG N, MELLERT W, et al. Application of metabolomics in vitro for identification of toxicological modes of action[J]. Toxicol Lett, 2013, 221(28):S194.

[30]

DU L, WANG H, XU W, et al. Application of ultraperformance liquid chromatography/mass spectrometry-based metabonomic techniques to analyze the joint toxic action of long-term lowlevel exposure to a mixture of organophosphate pesticides on rat urine profile[J]. Toxicol Sci, 2013, 134(1):195-206.

doi: 10.1093/toxsci/kft091 [31]

DU L, LI S, QI L, et al. Metabonomic analysis of the joint toxic action of long-term low-level exposure to a mixture of four organophosphate pesticides in rat plasma[J]. Mol BioSyst, 2014, 10(5):1153-1161.

doi: 10.1039/C4MB00044G [32]

VAN RAVENZWAAY B, HEROLD M, KAMP H, et al. Metabolomics:a tool for early detection of toxicological effects and an opportunity for biology based grouping of chemicalsfrom QSAR to QBAR[J]. Mutat Res/Genet Toxicol Environ Mutagen, 2012, 746(2):144-150.

doi: 10.1016/j.mrgentox.2012.01.006 [33]

CHEN C, KRAUSZ K W, SHAH Y M, et al. LC-MS-based metabolomics of acetaminophen-induced acute toxicity[J]. FASEB J, 2009, 23(1 Suppl):760-764.

[34]

ZHAO T, ZHANG H, ZHAO T, et al. Intrarenal metabolomics reveals the association of local organic toxins with the progression of diabetic kidney disease[J]. J Pharm Biomed Anal, 2012, 60:32-43.

doi: 10.1016/j.jpba.2011.11.010 [35]

HUANG S M, ZUO X B, LI J J, et al. Metabolomics studies show dose-dependent toxicity induced by SiO2 nanoparticles in MRC-5 human fetal lung fibroblasts[J]. Adv Healthc Mater, 2012, 1(6):779-784.

doi: 10.1002/adhm.v1.6 [36]

GARCIA-SEVILLANO M A, GARCIA-BARRERA T, GOMEZARIZA J L. Application of metallomic and metabolomic approaches in exposure experiments on laboratory mice for environmental metal toxicity assessment[J]. Metallomics:integrated biometal science, 2014, 6(2):237-248.

doi: 10.1039/c3mt00302g [37]

ROBERTSON D G, WATKINS P B, REILY M D. Metabolomics in toxicology:preclinical and clinical applications[J]. Toxicol Sci, 2011, 120(S1):S146-S170.

[38]

BOOTH S C, WORKENTINE M L, WELJIE A M, et al. Metabolomics and its application to studying metal toxicity[J]. Metallomics, 2011, 3(11):1142-1152.

doi: 10.1039/c1mt00070e [39]

GARCÍA-SEVILLANO M A, GARCÍA-BARRERA T, GÓMEZ-ARIZA J L. Application of metallomic and metabolomic approaches in exposure experiments on laboratory mice for environmental metal toxicity assessment[J]. Metallomics, 2014, 6(2):237-248.

doi: 10.1039/c3mt00302g [40]

ÁNGEL GARCÍA-SEVILLANO M, GARCÍA-BARRERA T, LUIS GÓMEZ-ARIZA J. Environmental metabolomics:biological markers for metal toxicity[J]. Electrophoresis, 2015, 36(18):2348-2365.

doi: 10.1002/elps.v36.18 [41]

VAN RAVENZWAAY B, MONTOYA G A, FABIAN E, et al. The sensitivity of metabolomics versus classical regulatory toxicology from a NOAEL perspective[J]. Toxicol Lett, 2014, 227(1):20-28.

doi: 10.1016/j.toxlet.2014.03.004 [42]

SHOCKCOR J P, HOLMES E. Metabonomic applications in toxicity screening and disease diagnosis[J]. Curr Top Med Chem, 2002, 2(1):35-51.

doi: 10.2174/1568026023394498 [43]

TAN Y, KO J, LIU X, et al. Serum metabolomics reveals betaine and phosphatidylcholine as potential biomarkers for the toxic responses of processed Aconitum carmichaelii Debx[J]. Mol BioSyst, 2014, 10(9):2305-2316.

doi: 10.1039/C4MB00072B [44]

YANG H, LIN W, ZHANG J, et al. Metabonomic analysis of the toxic effects of TM208 in rat urine by HPLC-ESI-IT-TOF/MS[J]. J Chromatogr B, 2014, 959:49-54.

doi: 10.1016/j.jchromb.2014.03.036 [45]

ZHANG Z, LU C, LIU X, et al. Global and targeted metabolomics reveal that bupleurotoxin, a toxic type of polyacetylene, induces cerebral lesion by inhibiting GABA receptor in mice[J]. J Proteome Res, 2014, 13(2):925-933.

doi: 10.1021/pr400968c [46]

ZENG Y, QI L, LI S, et al. A metabonomic analysis of the effect of quercetin on toxicity induced by chronic exposure to low-level dichlorvos in rat plasma[J]. Mol BioSyst, 2014, 10(10):2643-2653.

[47]

WANG P, WANG H P, XU M Y, et al. Combined subchronic toxicity of dichlorvos with malathion or pirimicarb in mice liver and serum:a metabonomic study[J]. Food Chem Toxicol, 2014, 70:222-230.

doi: 10.1016/j.fct.2014.05.027 [48]

GONZALEZ F J, FANG Z Z, MA X. Transgenic mice and metabolomics for study of hepatic xenobiotic metabolism and toxicity[J]. Expert Opin Drug Metab Toxicol, 2015, 11(6):869-881.

doi: 10.1517/17425255.2015.1032245 [49]

CORTASSA S, CACERES V, BELL L N, et al. From metabolomics to fluxomics:a computational procedure to translate metabolite profiles into metabolic fluxes[J]. Biophys J, 2015, 108(1):163-172.

doi: 10.1016/j.bpj.2014.11.1857