Application of Lipidomics in Toxicological Studies

doi:10.13560/j.cnki.biotech.bull.1985.2022-0793

Abstract

Abstract:

As major components of cells, lipids play important roles in a variety of life activities, such as intracellular material transport, signal transduction and apoptosis, etc. Lipidomics provides a systematic analysis of lipids in living organisms to understand their interactions and the interactions with other biomolecules. The authors mainly introduced the analysis methods of lipidomics, including the pretreatment methods of samples, detection methods and instruments, and data analysis methods. Besides that, the authors reviewed the research progress of lipidomics in neurotoxicity, hepatotoxicity, immunotoxicity and endocrine disrupting toxicity, aiming to provide ideas and reference for studying the mechanism of compound toxicity. Finally, the authors suggested that lipidomics technology should be used to study the combined toxic effects of different compounds in the future, to screen relevant lipid biomarkers based on the lipidomics, as well as to provide the scientific basis for risk warning of combined toxicity and relevant toxic mechanism study.

Key words: lipids, lipidomics, toxicology, analysis methods

WANG Xin-lu, WANG Meng, ZHAI Wen-lei. Application of Lipidomics in Toxicological Studies[J]. Biotechnology Bulletin, 2023, 39(3): 69-80.

Figures/Tables 4

References 77

[1]	Yang S, Qiao B, Lu SH, et al. Comparative lipidomics analysis of cellular development and apoptosis in two Taxus cell lines[J]. Biochim Biophys Acta, 2007, 1771(5): 600-612.
[2]	Wang XM. Lipid signaling[J]. Curr Opin Plant Biol, 2004, 7(3): 329-336. pmid: 15134755
[3]	Baumruker T, Bornancin F, Billich A. The role of sphingosine and ceramide kinases in inflammatory responses[J]. Immunol Lett, 2005, 96(2): 175-185. pmid: 15585321
[4]	Lock EA, Reed CJ, Kinsey GR, et al. Caspase-dependent and-independent induction of phosphatidylserine externalization during apoptosis in human renal carcinoma Cak(1)-1 and A-498 cells[J]. Toxicology, 2007, 229(1-2): 79-90. doi: 10.1016/j.tox.2006.10.003 URL
[5]	Ruscica M, Penson PE, Ferri N, et al. Impact of nutraceuticals on markers of systemic inflammation: potential relevance to cardiovascular diseases - A position paper from the International Lipid Expert Panel(ILEP)[J]. Prog Cardiovasc Dis, 2021, 67: 40-52. doi: 10.1016/j.pcad.2021.06.010 URL
[6]	Han MJ, Choung SY. Codonopsis lanceolata ameliorates sarcopenic obesity via recovering PI3K/Akt pathway and lipid metabolism in skeletal muscle[J]. Phytomedicine, 2022, 96: 153877. doi: 10.1016/j.phymed.2021.153877 URL
[7]	Rodríguez-Calvo R, Girona J, Rodríguez M, et al. Fatty acid binding protein 4(FABP4)as a potential biomarker reflecting myocardial lipid storage in type 2 diabetes[J]. Metabolism, 2019, 96: 12-21. doi: 10.1016/j.metabol.2019.04.007 URL
[8]	van der Linden RJ, Reus LM, de Witte W, et al. Genetic overlap between Alzheimer's disease and blood lipid levels[J]. Neurobiol Aging, 2021, 108: 189-195. doi: 10.1016/j.neurobiolaging.2021.06.019 pmid: 34340865
[9]	Parrales A, Iwakuma T. p53 as a regulator of lipid metabolism in cancer[J]. Int J Mol Sci, 2016, 17(12): 2074. doi: 10.3390/ijms17122074 URL
[10]	Han XL, Gross RW. Global analyses of cellular lipidomes directly from crude extracts of biological samples by ESI mass spectrometry: a bridge to lipidomics[J]. J Lipid Res, 2003, 44(6): 1071-1079. doi: 10.1194/jlr.R300004-JLR200 pmid: 12671038
[11]	王泓午, 赵紫薇, 曹姗, 等. 中国脂质组学研究现状的文献计量学分析[J]. 天津中医药, 2015, 32(2): 76-79.
	Wang HW, Zhao ZW, Cao S, et al. The bibliometric manalysis of lipidomics research in China[J]. Tianjin J Tradit Chin Med, 2015, 32(2): 76-79.
[12]	Wang XL, Qiu J, Xu YY, et al. Integrated non-targeted lipidomics and metabolomics analyses for fluctuations of neonicotinoids imidacloprid and acetamiprid on Neuro-2a cells[J]. Environ Pollut, 2021, 284: 117327. doi: 10.1016/j.envpol.2021.117327 URL
[13]	Tham YK, Bernardo BC, Huynh K, et al. Lipidomic profiles of the heart and circulation in response to exercise versus cardiac pathology: a resource of potential biomarkers and drug targets[J]. Cell Rep, 2018, 24(10): 2757-2772. doi: S2211-1247(18)31271-3 pmid: 30184508
[14]	Saito K. Application of comprehensive lipidomics to biomarker research on adverse drug reactions[J]. Drug Metab Pharmacokinet, 2021, 37: 100377. doi: 10.1016/j.dmpk.2020.100377 URL
[15]	Luque de Castro MD, Quiles-Zafra R. Lipidomics: an omics discipline with a key role in nutrition[J]. Talanta, 2020, 219: 121197. doi: 10.1016/j.talanta.2020.121197 URL
[16]	蔡潭溪, 刘平生, 杨福全, 等. 脂质组学研究进展[J]. 生物化学与生物物理进展, 2010, 37(2): 121-128.
	Cai TX, Liu PS, Yang FQ, et al. The research advances in the field of lipidomics[J]. Prog Biochem Biophys, 2010, 37(2): 121-128. doi: 10.3724/SP.J.1206.2009.00479 URL
[17]	宋诗瑶, 白玉, 刘虎威. 脂质组学分析中样品前处理技术的研究进展[J]. 色谱, 2020, 38(1): 66-73. doi: 10.3724/SP.J.1123.2019.07011
	Song SY, Bai Y, Liu HW. Advances in the development of the sample preparation techniques in lipidomics[J]. Chin J Chromatogr, 2020, 38(1): 66-73. doi: 10.3724/SP.J.1123.2019.07011
[18]	Folch J, Lees M, SLOANE STANLEY GH. A simple method for the isolation and purification of total lipides from animal tissues[J]. J Biol Chem, 1957, 226(1): 497-509. pmid: 13428781
[19]	Bligh EG, Dyer WJ. A rapid method of total lipid extraction and purification[J]. Can J Biochem Physiol, 1959, 37(8): 911-917. doi: 10.1139/o59-099 pmid: 13671378
[20]	Chen IS, Shen CSJ, Sheppard AJ. Comparison of methylene chloride and chloroform for the extraction of fats from food products[J]. J Am Oil Chem Soc, 1981, 58(5): 599-601. doi: 10.1007/BF02672373 URL
[21]	Matyash V, Liebisch G, Kurzchalia TV, et al. Lipid extraction by methyl-tert-butyl ether for high-throughput lipidomics[J]. J Lipid Res, 2008, 49(5): 1137-1146. doi: 10.1194/jlr.D700041-JLR200 pmid: 18281723
[22]	Calderón C, Sanwald C, Schlotterbeck J, et al. Comparison of simple monophasic versus classical biphasic extraction protocols for comprehensive UHPLC-MS/MS lipidomic analysis of Hela cells[J]. Anal Chim Acta, 2019, 1048: 66-74. doi: S0003-2670(18)31265-0 pmid: 30598159
[23]	Jin WB, Yang JN, Liu DY, et al. Determination of inflammation-related lipids in depressive rats by on-line supercritical fluid extraction-supercritical fluid chromatography-tandem mass spectrometry[J]. J Pharm Biomed Anal, 2021, 203: 114210. doi: 10.1016/j.jpba.2021.114210 URL
[24]	Mao GW, Qu F, St Croix CM, et al. Mitochondrial redox opto-lipidomics reveals mono-oxygenated cardiolipins as pro-apoptotic death signals[J]. ACS Chem Biol, 2016, 11(2): 530-540. doi: 10.1021/acschembio.5b00737 pmid: 26697918
[25]	胡聪, 吴琳静, 熊印华, 等. 脂质组学在肝脏疾病中的研究进展[J]. 中国药理学通报, 2021, 37(1): 6-12.
	Hu C, Wu LJ, Xiong YH, et al. Research progress of lipomics in liver diseases[J]. Chin Pharmacol Bull, 2021, 37(1): 6-12.
[26]	蔡教英, 欧阳克蕙, 上官新晨, 等. 脂质代谢组学的研究进展[J]. 动物营养学报, 2011, 23(11): 1870-1876.
	Cai JY, Ouyang KH, Shangguan XC, et al. Recent advances in lipidomics[J]. Chin J Animal Nutr, 2011, 23(11): 1870-1876.
[27]	Fuchs B, Süss R, Teuber K, et al. Lipid analysis by thin-layer chromatography—a review of the current state[J]. J Chromatogr A, 2011, 1218(19): 2754-2774. doi: 10.1016/j.chroma.2010.11.066 URL
[28]	Goto-Inoue N, Hayasaka T, Taki T, et al. A new lipidomics approach by thin-layer chromatography-blot-matrix-assisted laser desorption/ionization imaging mass spectrometry for analyzing detailed patterns of phospholipid molecular species[J]. J Chromatogr A, 2009, 1216(42): 7096-7101. doi: 10.1016/j.chroma.2009.08.056 pmid: 19740470
[29]	Wang XL, Xu YY, Song X, et al. Analysis of glycerophospholipid metabolism after exposure to PCB153 in PC12 cells through targeted lipidomics by UHPLC-MS/MS[J]. Ecotoxicol Environ Saf, 2019, 169: 120-127. doi: 10.1016/j.ecoenv.2018.11.006 URL
[30]	Abinaya B, Waseem M, Kashif M, et al. Lipidomics: an excellent tool for chronic disease detection[J]. Curr Res Transl Med, 2022, 70(4): 103346. doi: 10.1016/j.retram.2022.103346 URL
[31]	Liu ZQ, Zhao MT, Wang XW, et al. Investigation of oyster Crassostrea gigas lipid profile from three sea areas of China based on non-targeted lipidomics for their geographic region traceability[J]. Food Chem, 2022, 386: 132748. doi: 10.1016/j.foodchem.2022.132748 URL
[32]	Wang KW, Xu L, Wang X, et al. Discrimination of beef from different origins based on lipidomics: a comparison study of DART-QTOF and LC-ESI-QTOF[J]. LWT, 2021, 149: 111838. doi: 10.1016/j.lwt.2021.111838 URL
[33]	Shi T, Wu GC, Jin QZ, et al. Detection of camellia oil adulteration using chemometrics based on fatty acids GC fingerprints and phytosterols GC-MS fingerprints[J]. Food Chem, 2021, 352: 129422. doi: 10.1016/j.foodchem.2021.129422 URL
[34]	Zhang SM, Wang HB, Zhu MJ. A sensitive GC/MS detection method for analyzing microbial metabolites short chain fatty acids in fecal and serum samples[J]. Talanta, 2019, 196: 249-254. doi: S0039-9140(18)31316-X pmid: 30683360
[35]	李石磊, 张阳阳, 关明, 等. MALDIMSI在脂质组学研究中的应用[J]. 分析测试学报, 2017, 36(2): 170-177.
	Li SL, Zhang YY, Guan M, et al. Application of MALDI MSI in lipidomics research[J]. J Instrum Anal, 2017, 36(2): 170-177.
[36]	Manikandan M, Wu HF. Bio-mimicked gold nanoparticles with complex fetal bovine serum as sensors for single cell MALDI MS of cancer cell and cancer stem cell[J]. Sens Actuat B Chem, 2016, 231: 154-165. doi: 10.1016/j.snb.2016.02.060 URL
[37]	Zeng T, Zhang R, Chen YY, et al. In situ localization of lipids on mouse kidney tissues with acute cadmium toxicity using atmospheric pressure-MALDI mass spectrometry imaging[J]. Talanta, 2022, 245: 123466. doi: 10.1016/j.talanta.2022.123466 URL
[38]	Liu HX, Wang SQ, Lin JM, et al. Investigation of the lipidomic changes in differentiated glioblastoma cells after drug treatment using MALDI-MS[J]. Talanta, 2021, 233: 122570. doi: 10.1016/j.talanta.2021.122570 URL
[39]	Buszewska-Forajta M, Pomastowski P, Monedeiro F, et al. New approach in determination of urinary diagnostic markers for prostate cancer by MALDI-TOF/MS[J]. Talanta, 2022, 236: 122843. doi: 10.1016/j.talanta.2021.122843 URL
[40]	Rocha B, Cillero-Pastor B, Ruiz-Romero C, et al. Identification of a distinct lipidomic profile in the osteoarthritic synovial membrane by mass spectrometry imaging[J]. Osteoarthritis Cartilage, 2021, 29(5): 750-761. doi: 10.1016/j.joca.2020.12.025 URL
[41]	Chen YY, Wang T, Xie PS, et al. Mass spectrometry imaging revealed alterations of lipid metabolites in multicellular tumor spheroids in response to hydroxychloroquine[J]. Anal Chim Acta, 2021, 1184: 339011. doi: 10.1016/j.aca.2021.339011 URL
[42]	Marqueño A, Pérez-Albaladejo E, Denslow ND, et al. Untargeted lipidomics reveals the toxicity of bisphenol A bis(3-chloro-2- hydroxypropyl)ether and bisphenols A and F in zebrafish liver cells[J]. Ecotoxicol Environ Saf, 2021, 219: 112311. doi: 10.1016/j.ecoenv.2021.112311 URL
[43]	Yang CX, Wei JT, Cao GD, et al. Lipid metabolism dysfunction and toxicity of BDE-47 exposure in white adipose tissue revealed by the integration of lipidomics and metabolomics[J]. Sci Total Environ, 2022, 806(Pt 1): 150350. doi: 10.1016/j.scitotenv.2021.150350 URL
[44]	Cui CM, Zhu L, Wang Q, et al. A GC-MS-based untargeted metabolomics approach for comprehensive metabolic profiling of vancomycin-induced toxicity in mice[J]. Heliyon, 2022, 8(7): e09869. doi: 10.1016/j.heliyon.2022.e09869 URL
[45]	Duan YF, Zeng SM, Lu ZJ, et al. Responses of lipid metabolism and lipidomics in the hepatopancreas of Pacific white shrimp Litopenaeus vannamei to microcystin-LR exposure[J]. Sci Total Environ, 2022, 820: 153245. doi: 10.1016/j.scitotenv.2022.153245 URL
[46]	Zeng T, Guo WJ, Jiang LL, et al. Integration of omics analysis and atmospheric pressure MALDI mass spectrometry imaging reveals the cadmium toxicity on female ICR mouse[J]. Sci Total Environ, 2021, 801: 149803. doi: 10.1016/j.scitotenv.2021.149803 URL
[47]	Xu MM, Legradi J, Leonards P. Using comprehensive lipid profiling to study effects of PFHxS during different stages of early zebrafish development[J]. Sci Total Environ, 2022, 808: 151739. doi: 10.1016/j.scitotenv.2021.151739 URL
[48]	Zhang WW, Huo TG, Li AH, et al. Identification of neurotoxicity markers induced by realgar exposure in the mouse cerebral cortex using lipidomics[J]. J Hazard Mater, 2020, 389: 121567. doi: 10.1016/j.jhazmat.2019.121567 URL
[49]	Ji FF, Sreenivasmurthy SG, Wei JT, et al. Study of BDE-47 induced Parkinson's disease-like metabolic changes in C57BL/6 mice by integrated metabolomic, lipidomic and proteomic analysis[J]. J Hazard Mater, 2019, 378: 120738. doi: 10.1016/j.jhazmat.2019.06.015 URL
[50]	Wang CF, Deng HY, Wang DB, et al. Changes in metabolomics and lipidomics in brain tissue and their correlations with the gut microbiome after chronic food-derived arsenic exposure in mice[J]. Ecotoxicol Environ Saf, 2021, 228: 112935. doi: 10.1016/j.ecoenv.2021.112935 URL
[51]	Wang CY, Liu F, Frisch-Daiello JL, et al. Lipidomics reveals a systemic energy deficient state that precedes neurotoxicity in neonatal monkeys after sevoflurane exposure[J]. Anal Chim Acta, 2018, 1037: 87-96. doi: S0003-2670(17)31330-2 pmid: 30292318
[52]	Yang Y, Sun FJ, Chen HJ, et al. Postnatal exposure to DINP was associated with greater alterations of lipidomic markers for hepatic steatosis than DEHP in postweaning mice[J]. Sci Total Environ, 2021, 758: 143631. doi: 10.1016/j.scitotenv.2020.143631 URL
[53]	Xu L, Zhao QW, Luo J, et al. Integration of proteomics, lipidomics, and metabolomics reveals novel metabolic mechanisms underlying N, N-dimethylformamide induced hepatotoxicity[J]. Ecotoxicol Environ Saf, 2020, 205: 111166. doi: 10.1016/j.ecoenv.2020.111166 URL
[54]	Menéndez-Pedriza A, Jaumot J, Bedia C. Lipidomic analysis of single and combined effects of polyethylene microplastics and polychlorinated biphenyls on human hepatoma cells[J]. J Hazard Mater, 2022, 421: 126777. doi: 10.1016/j.jhazmat.2021.126777 URL
[55]	Li X, Li T, Wang ZP, et al. Distribution of perfluorooctane sulfonate in mice and its effect on liver lipidomic[J]. Talanta, 2021, 226: 122150. doi: 10.1016/j.talanta.2021.122150 URL
[56]	韩运祺, 肖云峰, 钱新宇, 等. 药物毒理学的研究进展[J]. 中国药理学与毒理学杂志, 2019, 33(10):835.
	Han YQ, Xiao YF, Qian XY, et al. Research advances of drug toxicology[J]. Chin J Pharmacol Toxicol, 2019, 33(10):835.
[57]	耿柠波, 任晓倩, 张海军, 等. 蛋白质组学在环境毒理学中的研究进展[J]. 生态毒理学报, 2020, 15(4): 88-98.
	Geng NB, Ren XQ, Zhang HJ, et al. A review on the application of proteomic approaches in environmental toxicology[J]. Asian J Ecotoxicol, 2020, 15(4): 88-98.
[58]	Zhao C, Tang Z, Yan JC, et al. Bisphenol S exposure modulate macrophage phenotype as defined by cytokines profiling, global metabolomics and lipidomics analysis[J]. Sci Total Environ, 2017, 592: 357-365. doi: 10.1016/j.scitotenv.2017.03.035 URL
[59]	Li R, Guo C, Lin X, et al. Integrative omics analyses uncover the mechanism underlying the immunotoxicity of perfluorooctanesulfonate in human lymphocytes[J]. Chemosphere, 2020, 256: 127062. doi: 10.1016/j.chemosphere.2020.127062 URL
[60]	Yang X, Chen WY, Gong Y, et al. A target lipidomics approach to investigate the acute inflammatory irritation induced by indolealkylamines from Chansu water fraction in rats[J]. Chin J Nat Med, 2021, 19(11): 856-867.
[61]	Wei JT, Li XN, Xiang L, et al. Metabolomics and lipidomics study unveils the impact of polybrominated diphenyl ether-47 on breast cancer mice[J]. J Hazard Mater, 2020, 390: 121451. doi: 10.1016/j.jhazmat.2019.121451 URL
[62]	Jungnickel H, Potratz S, Baumann S, et al. Identification of lipidomic biomarkers for coexposure to subtoxic doses of benzo[a]Pyrene and cadmium: the toxicological cascade biomarker approach[J]. Environ Sci Technol, 2014, 48(17): 10423-10431. doi: 10.1021/es502419w pmid: 25093272
[63]	Dai CS, Tang SS, Biao X, et al. Colistin induced peripheral neurotoxicity involves mitochondrial dysfunction and oxidative stress in mice[J]. Mol Biol Rep, 2019, 46(2): 1963-1972. doi: 10.1007/s11033-019-04646-5 pmid: 30783935
[64]	Cristaldi A, Fiore M, Oliveri Conti G, et al. Possible association between PM 2.5 and neurodegenerative diseases: a systematic review[J]. Environ Res, 2022, 208: 112581. doi: 10.1016/j.envres.2021.112581 URL
[65]	Piomelli D, Astarita G, Rapaka R. A neuroscientist's guide to lipidomics[J]. Nat Rev Neurosci, 2007, 8(10): 743-754. pmid: 17882252
[66]	Kim TH, Kim YW, Shin SM, et al. Synergistic hepatotoxicity of N, N-dimethylformamide with carbon tetrachloride in association with endoplasmic Reticulum stress[J]. Chem Biol Interact, 2010, 184(3): 492-501. doi: 10.1016/j.cbi.2010.01.029 URL
[67]	Chen MY, Bai MR, Yi YD, et al. Upregulation of hepatic CD36 via glucocorticoid receptor activation contributes to dexamethasone-induced liver lipid metabolism disorder in mice[J]. Toxicol Lett, 2022, 363: 1-10. doi: 10.1016/j.toxlet.2022.05.003 pmid: 35589016
[68]	Yang F, Dai YY, Min CT, et al. Neonatal overfeeding induced glucocorticoid overexposure accelerates hepatic lipogenesis in male rats[J]. Nutr Metab(Lond), 2018, 15: 30.
[69]	Fai Tse WK, Li JW, Kwan Tse AC, et al. Fatty liver disease induced by perfluorooctane sulfonate: novel insight from transcriptome analysis[J]. Chemosphere, 2016, 159: 166-177. doi: S0045-6535(16)30707-X pmid: 27289203
[70]	Kataria A, Trachtman H, Malaga-Dieguez L, et al. Association between perfluoroalkyl acids and kidney function in a cross-sectional study of adolescents[J]. Environ Health, 2015, 14: 89. doi: 10.1186/s12940-015-0077-9 URL
[71]	Lai KP, Lee JCY, Wan HT, et al. Effects of in utero PFOS exposure on transcriptome, lipidome, and function of mouse testis[J]. Environ Sci Technol, 2017, 51(15): 8782-8794. doi: 10.1021/acs.est.7b02102 pmid: 28654245
[72]	刘嫄淑, 王振涛. 免疫反应在心血管疾病中的作用及中药干预研究进展[J]. 中医临床研究, 2022, 14(13): 137-140.
	Liu YS, Wang ZT. A review on the role of immune response in cardiovascular disease and TCM material intervention[J]. Clin J Chin Med, 2022, 14(13): 137-140.
[73]	杨超超, 潘鹏涛, 谭婷, 等. 内分泌干扰物对鱼类性腺干扰的分子作用机制[J]. 延安大学学报: 自然科学版, 2021, 40(3): 27-32.
	Yang CC, Pan PT, Tan T, et al. Molecular mechanism of endocrine disruptors interfering with fish gonads[J]. J Yan’an Univ Nat Sci Ed, 2021, 40(3): 27-32.
[74]	Kajta M, Wójtowicz AK. Impact of endocrine-disrupting chemicals on neural development and the onset of neurological disorders[J]. Pharmacol Rep, 2013, 65(6): 1632-1639. pmid: 24553011
[75]	Jeng HA. Exposure to endocrine disrupting chemicals and male reproductive health[J]. Front Public Health, 2014, 2: 55. doi: 10.3389/fpubh.2014.00055 pmid: 24926476
[76]	Bedia C, Dalmau N, Jaumot J, et al. Phenotypic malignant changes and untargeted lipidomic analysis of long-term exposed prostate cancer cells to endocrine disruptors[J]. Environ Res, 2015, 140: 18-31. doi: 10.1016/j.envres.2015.03.014 pmid: 25817993
[77]	李欣慧, 赵飞, 徐倩茹, 等. 内分泌干扰物对机体脂质代谢的影响及其机制研究进展[J]. 生态毒理学报, 2021, 16(3): 52-65.
	Li XH, Zhao F, Xu QR, et al. Research progress on effects of endocrine disrupting chemicals on lipid metabolism of organisms and underlying mechanisms[J]. Asian J Ecotoxicol, 2021, 16(3): 52-65.

序号 No.	样品类别 Sample type	提取方式 Extraction method	分析仪器 Analysis instrument	毒性研究目标物 Toxicity research target	参考文献 Reference
1	斑马鱼肝细胞	氯仿/甲醇（2:1，V/V）+0.01%丁羟甲苯	UHPLC-Q Exactive-MS	双酚A、双酚F、双酚3-氯-2-羟丙基醚	[42]
2	C57BL/6J鼠	甲基叔丁基醚/甲醇/水（10:3:3，V/V/V）	LC-MS/MS	多溴联苯醚	[43]
3	雄性昆明鼠血清	十七烷酸/甲醇（7:2，V/V）	GC-MS	万古霉素	[44]
4	太平洋白虾	氯仿-甲醇体系	LC-MS/MS	微囊藻素	[45]
5	PC12细胞	二氯甲烷/甲醇（1:2，V/V）	UHPLC-MS/MS	多氯联苯（PCB153）	[29]
6	雌性ICR小鼠	氯仿/甲醇/水（3:4:1，V/V/V）	AP-MALDI-MS	镉	[46]
7	斑马鱼胚胎	氯仿/甲醇/水（2:1:1，V/V/V）	LC-QTOF-MS	全氟己烷磺酸	[47]
8	小鼠大脑皮层	甲醇/甲基叔丁基醚（3:10，V/V）	UHPLC-Q Exactive plus-MS	雄黄	[48]
9	小鼠脑组织	甲醇/甲基叔丁基醚（3:10，V/V）	LC-MS/MS	多溴联苯醚（BDE-47）	[49]
10	小鼠脑组织、血液、粪便	甲醇/甲基叔丁基醚（1:5，V/V）	UHPLC-Q Exactive Focus-MS	砷	[50]
11	猕猴血清、脑组织	氯仿/甲醇/水（1:2:0.8，V/V/V）	LC-MS/MS	七氟烷	[51]
12	Neuro-2a细胞	二氯甲烷/甲醇（1:2，V/V）	UHPLC-Q Exactive plus-MS	吡虫啉、啶虫脒	[12]
13	小鼠肝脏组织	氯仿/甲醇（2:1，V/V）	LC-MS/MS	邻苯二甲酸酯	[52]
14	人肝细胞	甲醇/甲基叔丁基醚	UHPLC-Q Exactive-MS	二甲基甲酰胺	[53]
15	HepG2细胞	甲醇/甲基叔丁基醚（1:3，V/V）	LC-QTOF-MS	聚乙烯微塑料、多氯联苯	[54]
16	小鼠肝脏组织	甲醇	UPLC-ESI-Orbitrap-MS	全氟己烷磺酸	[55]

序号 No.	样品类别 Sample type	提取方式 Extraction method	分析仪器 Analysis instrument	毒性研究目标物 Toxicity research target	参考文献 Reference
1	斑马鱼肝细胞	氯仿/甲醇（2:1，V/V）+0.01%丁羟甲苯	UHPLC-Q Exactive-MS	双酚A、双酚F、双酚3-氯-2-羟丙基醚	[42]
2	C57BL/6J鼠	甲基叔丁基醚/甲醇/水（10:3:3，V/V/V）	LC-MS/MS	多溴联苯醚	[43]
3	雄性昆明鼠血清	十七烷酸/甲醇（7:2，V/V）	GC-MS	万古霉素	[44]
4	太平洋白虾	氯仿-甲醇体系	LC-MS/MS	微囊藻素	[45]
5	PC12细胞	二氯甲烷/甲醇（1:2，V/V）	UHPLC-MS/MS	多氯联苯（PCB153）	[29]
6	雌性ICR小鼠	氯仿/甲醇/水（3:4:1，V/V/V）	AP-MALDI-MS	镉	[46]
7	斑马鱼胚胎	氯仿/甲醇/水（2:1:1，V/V/V）	LC-QTOF-MS	全氟己烷磺酸	[47]
8	小鼠大脑皮层	甲醇/甲基叔丁基醚（3:10，V/V）	UHPLC-Q Exactive plus-MS	雄黄	[48]
9	小鼠脑组织	甲醇/甲基叔丁基醚（3:10，V/V）	LC-MS/MS	多溴联苯醚（BDE-47）	[49]
10	小鼠脑组织、血液、粪便	甲醇/甲基叔丁基醚（1:5，V/V）	UHPLC-Q Exactive Focus-MS	砷	[50]
11	猕猴血清、脑组织	氯仿/甲醇/水（1:2:0.8，V/V/V）	LC-MS/MS	七氟烷	[51]
12	Neuro-2a细胞	二氯甲烷/甲醇（1:2，V/V）	UHPLC-Q Exactive plus-MS	吡虫啉、啶虫脒	[12]
13	小鼠肝脏组织	氯仿/甲醇（2:1，V/V）	LC-MS/MS	邻苯二甲酸酯	[52]
14	人肝细胞	甲醇/甲基叔丁基醚	UHPLC-Q Exactive-MS	二甲基甲酰胺	[53]
15	HepG2细胞	甲醇/甲基叔丁基醚（1:3，V/V）	LC-QTOF-MS	聚乙烯微塑料、多氯联苯	[54]
16	小鼠肝脏组织	甲醇	UPLC-ESI-Orbitrap-MS	全氟己烷磺酸	[55]

序号 No.	研究对象 Research object	毒性作用类型 Toxicity effect category	差异脂质 Differential lipids	参考文献 Reference
1	小鼠脑组织	神经毒性	AcCa（14:0）、Cer（d18:1/21:0）、DG（16:0/16:0）等	[50]
2	小鼠脑组织、血液、粪便	神经毒性	PE（18:0/0:0）、PC（18:1/22:6）、PC（18:0/22:5）等	[51]
3	猕猴血清、脑组织	神经毒性	16:1 LPG、18:0-20:4 PC、18:0 LPI等	[52]
4	Neuro-2a细胞	神经毒性	MePC（33:0e）、PC（40:7）、ChE（20:4）等	[12]
5	小鼠肝脏组织	肝脏毒性	DG（16:0/16:0）、DG（16:0/20:4）、TG（16:0/18:2/18:2）等	[52]
6	人肝细胞	肝脏毒性	TG（18:1/22:6/22:6）、TG（20:2/22:6/22:6）、PE（18:0/22:6）等	[53]
7	HepG2细胞	肝脏毒性	Cer（42:3）、HexosylCer（32:1）、SM（32:1）等	[54]
8	小鼠肝脏组织	肝脏毒性	LPC18:1、PI（18:0/22:5）、PC（18:0/20:2）等	[55]
9	ZFL细胞（斑马鱼肝脏细胞）	肝脏毒性	LPE（18:1）、LPC（18:1）等	[42]
10	巨噬细胞	免疫毒性	SM（d18:0/16:0）、Cer（d18:1/20:0）、PC（20:1/14:1）等	[58]
11	人淋巴细胞	免疫毒性	TG（16:0/16:1/18:2）、DG（18:2/22:6）、PC（P-14:0/24:4）等	[59]
12	成年雄性大鼠	免疫毒性	PGJ2、PGF2α、PGE2等	[52]
13	DU145前列腺癌细胞	内分泌干扰毒性	PA（32:0）、LacCer（d18:1/24:0）、CL（68:2）等	[60]
14	MDA-MB-231细胞、雌性裸鼠	内分泌干扰毒性	PC（36:1）、DG（18:1/18:2）、PE（18:0/20:4）等	[61]
15	MCF-7细胞	内分泌干扰毒性	SM（16:0）、Lyso PC（16:0）、PC（32:1）等	[62]

序号 No.	研究对象 Research object	毒性作用类型 Toxicity effect category	差异脂质 Differential lipids	参考文献 Reference
1	小鼠脑组织	神经毒性	AcCa（14:0）、Cer（d18:1/21:0）、DG（16:0/16:0）等	[50]
2	小鼠脑组织、血液、粪便	神经毒性	PE（18:0/0:0）、PC（18:1/22:6）、PC（18:0/22:5）等	[51]
3	猕猴血清、脑组织	神经毒性	16:1 LPG、18:0-20:4 PC、18:0 LPI等	[52]
4	Neuro-2a细胞	神经毒性	MePC（33:0e）、PC（40:7）、ChE（20:4）等	[12]
5	小鼠肝脏组织	肝脏毒性	DG（16:0/16:0）、DG（16:0/20:4）、TG（16:0/18:2/18:2）等	[52]
6	人肝细胞	肝脏毒性	TG（18:1/22:6/22:6）、TG（20:2/22:6/22:6）、PE（18:0/22:6）等	[53]
7	HepG2细胞	肝脏毒性	Cer（42:3）、HexosylCer（32:1）、SM（32:1）等	[54]
8	小鼠肝脏组织	肝脏毒性	LPC18:1、PI（18:0/22:5）、PC（18:0/20:2）等	[55]
9	ZFL细胞（斑马鱼肝脏细胞）	肝脏毒性	LPE（18:1）、LPC（18:1）等	[42]
10	巨噬细胞	免疫毒性	SM（d18:0/16:0）、Cer（d18:1/20:0）、PC（20:1/14:1）等	[58]
11	人淋巴细胞	免疫毒性	TG（16:0/16:1/18:2）、DG（18:2/22:6）、PC（P-14:0/24:4）等	[59]
12	成年雄性大鼠	免疫毒性	PGJ2、PGF2α、PGE2等	[52]
13	DU145前列腺癌细胞	内分泌干扰毒性	PA（32:0）、LacCer（d18:1/24:0）、CL（68:2）等	[60]
14	MDA-MB-231细胞、雌性裸鼠	内分泌干扰毒性	PC（36:1）、DG（18:1/18:2）、PE（18:0/20:4）等	[61]
15	MCF-7细胞	内分泌干扰毒性	SM（16:0）、Lyso PC（16:0）、PC（32:1）等	[62]