Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids

Limei Li; Qingce Zang; Xinzhu Li; Ying Zhu; Shanjing Wen; Jiuming He; Ruiping Zhang; Zeper Abliz

doi:10.1016/j.jpha.2023.04.007

Volume 13 Issue 5

May 2023

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Article Navigation > Journal of Pharmaceutical Analysis > 2023 > 13(5): 483-493

Limei Li, Qingce Zang, Xinzhu Li, Ying Zhu, Shanjing Wen, Jiuming He, Ruiping Zhang, Zeper Abliz. Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids[J]. Journal of Pharmaceutical Analysis, 2023, 13(5): 483-493. doi: 10.1016/j.jpha.2023.04.007

Citation:

Limei Li, Qingce Zang, Xinzhu Li, Ying Zhu, Shanjing Wen, Jiuming He, Ruiping Zhang, Zeper Abliz. Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids[J]. Journal of Pharmaceutical Analysis, 2023, 13(5): 483-493. doi: 10.1016/j.jpha.2023.04.007

Citation:

Limei Li, Qingce Zang, Xinzhu Li, Ying Zhu, Shanjing Wen, Jiuming He, Ruiping Zhang, Zeper Abliz. Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids[J]. Journal of Pharmaceutical Analysis, 2023, 13(5): 483-493. doi: 10.1016/j.jpha.2023.04.007

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Spatiotemporal pharmacometabolomics based on ambient mass spectrometry imaging to evaluate the metabolism and hepatotoxicity of amiodarone in HepG2 spheroids

doi: 10.1016/j.jpha.2023.04.007

a. State Key Laboratory of Bioactive Substance and Function of Natural Medicines, Institute of Materia Medica, Chinese Academy of Medical Sciences and Peking Union Medical College, Beijing, 100050, China;
b. Key Laboratory of Mass Spectrometry Imaging and Metabolomics (Minzu University of China), National Ethnic Affairs Commission, Beijing, 100081, China;
c. Center for Imaging and Systems Biology, College of Life and Environmental Sciences, Minzu University of China, Beijing, 100081, China

Funds:

This research was funded by the National Natural Science Foundation of China (Grant No.: 21874156), and the Chinese Academy of Medical Science (CAMS) Innovation Fund for Medical Sciences (Grant No.: 2021-1-I2M-028).

Received Date: Jan. 10, 2023
Accepted Date: Apr. 12, 2023
Rev Recd Date: Mar. 26, 2023
Publish Date: Apr. 14, 2023

Abstract

Abstract

Three-dimensional (3D) cell spheroid models combined with mass spectrometry imaging (MSI) enables innovative investigation of in vivo-like biological processes under different physiological and pathological conditions. Herein, airflow-assisted desorption electrospray ionization-MSI (AFADESI-MSI) was coupled with 3D HepG2 spheroids to assess the metabolism and hepatotoxicity of amiodarone (AMI). High-coverage imaging of >1100 endogenous metabolites in hepatocyte spheroids was achieved using AFADESI-MSI. Following AMI treatment at different times, 15 metabolites of AMI involved in N-desethylation, hydroxylation, deiodination, and desaturation metabolic reactions were identified, and according to their spatiotemporal dynamics features, the metabolic pathways of AMI were proposed. Subsequently, the temporal and spatial changes in metabolic disturbance within spheroids caused by drug exposure were obtained via metabolomic analysis. The main dysregulated metabolic pathways included arachidonic acid and glycerophospholipid metabolism, providing considerable evidence for the mechanism of AMI hepatotoxicity. In addition, a biomarker group of eight fatty acids was selected that provided improved indication of cell viability and could characterize the hepatotoxicity of AMI. The combination of AFADESI-MSI and HepG2 spheroids can simultaneously obtain spatiotemporal information for drugs, drug metabolites, and endogenous metabolites after AMI treatment, providing an effective tool for in vitro drug hepatotoxicity evaluation.
- Mass spectrometry imaging,
- HepG2 spheroids,
- Hepatotoxicity,
- Drug metabolism,
- Amiodarone

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References(46)

References

A.S. Serras, J.S. Rodrigues, M. Cipriano, et al., A critical perspective on 3D liver models for drug metabolism and toxicology studies, Front. Cell Dev. Biol. 9 (2021), 626805.

V.M. Lauschke, D.F.G. Hendriks, C.C. Bell, et al., Novel 3D culture systems for studies of human liver function and assessments of the hepatotoxicity of drugs and drug candidates, Chem. Res. Toxicol. 29 (2016) 1936-1955.

D. Zhang, G. Luo, X. Ding, et al., Preclinical experimental models of drug metabolism and disposition in drug discovery and development, Acta Pharm. Sin. B 2 (2012) 549-561.

M.J. Gomez-Lechon, L. Tolosa, I. Conde, et al., Competency of different cell models to predict human hepatotoxic drugs, Expet Opin. Drug Metabol. Toxicol. 10 (2014) 1553-1568.

R. Nudischer, K. Renggli, A. Hierlemann, et al., Characterization of a long-term mouse primary liver 3D tissue model recapitulating innate-immune responses and drug-induced liver toxicity, PLoS One 15 (2020), e0235745.

L. Kuna, I. Bozic, T. Kizivat, et al., Models of drug induced liver injury (DILI) - current issues and future perspectives, Curr. Drug Metabol. 19 (2018) 830-838.

A. Segovia-Zafra, D.E. Di Zeo-Sanchez, C. Lopez-Gomez, et al., Preclinical models of idiosyncratic drug-induced liver injury (iDILI): Moving towards prediction, Acta Pharm. Sin. B 11 (2021) 3685-3726.

M.J. Gomez-Lechon, A. Lahoz, L. Gombau, et al., In vitro evaluation of potential hepatotoxicity induced by drugs, Against Curr. Pharm. Des. 16 (2010) 1963-1977.

J. Liu, R. Li, R. Xue, et al., Liver extracellular matrices bioactivated hepatic spheroids as a model system for drug hepatotoxicity evaluations, Adv. Biosyst. 2 (2018), 1800110.

O.J. Trask Jr, A. Moore, E.L. LeCluyse, A micropatterned hepatocyte coculture model for assessment of liver toxicity using high-content imaging analysis, Assay Drug Dev. Technol. 12 (2014) 16-27.

M.T. Donato, A. Martinez-Romero, N. Jimenez, et al., Cytometric analysis for drug-induced steatosis in HepG2 cells, Chem. Biol. Interact. 181 (2009) 417-423.

L. Pan, P. Han, S. Ma, et al., Abnormal metabolism of gut microbiota reveals the possible molecular mechanism of nephropathy induced by hyperuricemia, Acta Pharm. Sin. B 10 (2020) 249-261.

A.M. Araujo, M. Carvalho, F. Carvalho, et al., Metabolomic approaches in the discovery of potential urinary biomarkers of drug-induced liver injury (DILI), Crit. Rev. Toxicol. 47 (2017) 638-654.

L. Goracci, A. Valeri, S. Sciabola, et al., A novel lipidomics-based approach to evaluating the risk of clinical hepatotoxicity potential of drugs in 3D human microtissues, Chem. Res. Toxicol. 33 (2020) 258-270.

D. Wang, D. Li, Y. Zhang, et al., Functional metabolomics reveal the role of AHR/GPR35 mediated kynurenic acid gradient sensing in chemotherapy-induced intestinal damage, Acta Pharm. Sin. B 11 (2021) 763-780.

L. Wang, Q. Zang, Y. Zhu, et al., On-tissue chemical oxidation followed by derivatization for mass spectrometry imaging enables visualization of primary and secondary hydroxyl-containing metabolites in biological tissues, Anal. Chem. 95 (2023) 1975-1984.

T. Greer, R. Sturm, L. Li, Mass spectrometry imaging for drugs and metabolites, J. Proteonomics 74 (2011) 2617-2631.

A. Nilsson, R.J.A. Goodwin, M. Shariatgorji, et al., Mass spectrometry imaging in drug development, Anal. Chem. 87 (2015) 1437-1455.

Z. Wang, W. Fu, M. Huo, et al., Spatial-resolved metabolomics reveals tissue-specific metabolic reprogramming in diabetic nephropathy by using mass spectrometry imaging, Acta Pharm. Sin. B 11 (2021) 3665-3677.

M. Huo, Z. Wang, W. Fu, et al., Spatially resolved metabolomics based on air-flow-assisted desorption electrospray ionization-mass spectrometry imaging reveals region-specific metabolic alterations in diabetic encephalopathy, J. Proteome Res. 20 (2021) 3567-3579.

Z. Wang, B. He, Y. Liu, et al., In situ metabolomics in nephrotoxicity of aristolochic acids based on air flow-assisted desorption electrospray ionization mass spectrometry imaging, Acta Pharm. Sin. B 10 (2020) 1083-1093.

X. Liu, A.B. Hummon, Mass spectrometry imaging of therapeutics from animal models to three-dimensional cell cultures, Anal. Chem. 87 (2015) 9508-9519.

L.E. Flint, G. Hamm, J.D. Ready, et al., Characterization of an aggregated three-dimensional cell culture model by multimodal mass spectrometry imaging, Anal. Chem. 92 (2020) 12538-12547.

P. Xie, H. Zhang, P. Wu, et al., Three-dimensional mass spectrometry imaging reveals distributions of lipids and the drug metabolite associated with the enhanced growth of colon cancer cell spheroids treated with triclosan, Anal. Chem. 94 (2022) 13667-13675.

M. Machalkova, B. Pavlatovska, J. Michalek, et al., Drug penetration analysis in 3D cell cultures using fiducial-based semiautomatic coregistration of MALDI MSI and immunofluorescence images, Anal. Chem. 91 (2019) 13475-13484.

X. Liu, J.K. Lukowski, C. Flinders, et al., MALDI-MSI of immunotherapy: Mapping the EGFR-targeting antibody cetuximab in 3D colon-cancer cell cultures, Anal. Chem. 90 (2018) 14156-14164.

Q. Zang, C. Sun, X. Chu, et al., Spatially resolved metabolomics combined with multicellular tumor spheroids to discover cancer tissue relevant metabolic signatures, Anal. Chim. Acta 1155 (2021), 338342.

P. Xie, X. Liang, Y. Song, et al., Mass spectrometry imaging combined with metabolomics revealing the proliferative effect of environmental pollutants on multicellular tumor spheroids, Anal. Chem. 92 (2020) 11341-11348.

Y. Chen, T. Wang, P. Xie, et al., Mass spectrometry imaging revealed alterations of lipid metabolites in multicellular tumor spheroids in response to hydroxychloroquine, Anal. Chim. Acta 1184 (2021), 339011.

H. Liu, F. Xu, Y. Gao, et al., An integrated LC-MS/MS strategy for quantifying the oxidative-redox metabolome in multiple biological samples, Anal. Chem. 92 (2020) 8810-8818.

R.P. Goodman, S.E. Calvo, V.K. Mootha, Spatiotemporal compartmentalization of hepatic NADH and NADPH metabolism, J. Biol. Chem. 293 (2018) 7508-7516.

M. Babatin, S.S. Lee, P.T. Pollak, Amiodarone hepatotoxicity, Curr. Vasc. Pharmacol. 6 (2008) 228-236.

S. Endo, Y. Toyoda, T. Fukami, et al., Stimulation of human monocytic THP-1 cells by metabolic activation of hepatotoxic drugs, Drug Metabol. Pharmacokinet. 27 (2012) 621-630.

K.M. Waldhauser, M. Torok, H.R. Ha, et al., Hepatocellular toxicity and pharmacological effect of amiodarone and amiodarone derivatives, J. Pharmacol. Exp. Therapeut. 319 (2006) 1413-1423.

J. He, C. Sun, T. Li, et al., A sensitive and wide coverage ambient mass spectrometry imaging method for functional metabolites based molecular histology, Adv. Sci. 5 (2018), 1800250.

C.R. Thoma, M. Zimmermann, I. Agarkova, et al., 3D cell culture systems modeling tumor growth determinants in cancer target discovery, Adv. Drug Deliv. Rev. 69-70 (2014) 29-41.

S. Nath, G.R. Devi, Three-dimensional culture systems in cancer research: Focus on tumor spheroid model, Pharmacol. Ther. 163 (2016) 94-108.

H.R. Ha, L. Bigler, B. Wendt, et al., Identification and quantitation of novel metabolites of amiodarone in plasma of treated patients, Eur. J. Pharmaceut. Sci. 24 (2005) 271-279.

P. Deng, T. You, X. Chen, et al., Identification of amiodarone metabolites in human bile by ultraperformance liquid chromatography/quadrupole time-of-flight mass spectrometry, Drug Metab. Dispos. 39 (2011) 1058-1069.

E.S. Jeong, G. Kim, D. Yim, et al., Identification and characterization of amiodarone metabolites in rats using UPLC-ESI-QTOFMS-based untargeted metabolomics approach, J. Toxicol. Environ. Health 81 (2018) 481-492.

M.R. Ghovanloo, M. Abdelsayed, P.C. Ruben, Effects of amiodarone and N-desethylamiodarone on cardiac voltage-gated sodium channels, Front. Pharmacol. 7 (2016), 39.

S. Nithiyanandam, S. Evan Prince, Toxins mechanism in instigating hepatotoxicity, Toxin Rev. 40 (2021) 616-631.

Y. Xue, Q. Deng, Q. Zhang, et al., Gigantol ameliorates CCl4-induced liver injury via preventing activation of JNK/cPLA2/12-LOX inflammatory pathway, Sci. Rep. 10 (2020), 22265.

Z. Yang, M. Jiang, Z. Yue, et al., Metabonomics analysis of semen euphorbiae and semen Euphorbiae Pulveratum using UPLC-Q-TOF/MS, Biomed. Chromatogr. 36 (2022), e5279.

S.A. Scott, T.P. Mathews, P.T. Ivanova, et al., Chemical modulation of glycerolipid signaling and metabolic pathways, Biochim. Biophys. Acta 1841 (2014) 1060-1084.

L.S. Csaki, J.R. Dwyer, L.G. Fong, et al., Lipins, lipinopathies, and the modulation of cellular lipid storage and signaling, Prog. Lipid Res. 52 (2013) 305-316.

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