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Мультифотонная микроскопия и масс-спектрометрия в прижизненном выявлении метаболической гетерогенности гепатоцитов

Мультифотонная микроскопия и масс-спектрометрия в прижизненном выявлении метаболической гетерогенности гепатоцитов

С.А. Родимова, Д.С. Кузнецова, Н.В. Бобров, А.А. Гулин, А.А. Васин, М.В. Губина, В.И. Щеславский, В.В. Елагин, М.М. Карабут, В.Е. Загайнов, Е.В. Загайнова
Ключевые слова: гетерогенность гепатоцитов; метаболический статус гепатоцитов; мультифотонная микроскопия; FLIM; TоF-SIMS.
2021, том 13, номер 2, стр. 18.

Полный текст статьи

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Цель исследования — оценить возможность выявления гетерогенности гепатоцитов по метаболическому статусу в нормальной печени с применением современных методов мультифотонной микроскопии и масс-спектрометрии.

Материалы и методы. Степень гетерогенности гепатоцитов по общей метаболической активности оценивали с применением метода мультифотонной микроскопии на основе данных об интенсивности автофлуоресценции внутриклеточных кофакторов НАД(Ф)Н и ФАД. Гетерогенность гепатоцитов по интенсивности внутриклеточных метаболических процессов определяли с помощью метода время-разрешенного имиджинга (FLIM — fluorescence lifetime imaging) на основе данных о вкладах времен жизни флуо­ресценции различных форм кофактора НАД(Ф)Н. Методом времяпролетной масс-спектрометрии вторичных ионов (TоF-SIMS — time-of-flight secondary ion mass spectrometry) проведено исследование липидного и аминокислотного состава гепатоцитов.

Результаты. Методом мультифотонной микроскопии выявлена гетерогенность гепатоцитов по общей метаболической активности. С применением FLIM установлена высокая степень гетерогенности по интенсивности процессов окислительного фосфорилирования, гликолиза и синтетических процессов (липогенеза, синтеза нуклеиновых кислот и пентозофосфатного пути). Методом TоF-SIMS выявлено наличие гетерогенности гепатоцитов по аминокислотному и липидному составам, что указывает на различную интенсивность синтетических процессов отдельных гепатоцитов. Кроме того, установлены различия в содержании PO3-ионов. Результаты TоF-SIMS-исследования согласуются с данными мультифотонной микроскопии и FLIM, подтверждая выявленную гетерогенность гепатоцитов по общей метаболической активности, а также по интенсивности внутриклеточных метаболических процессов.

Заключение. Используемые в работе новейшие методы флуоресцентного биоимиджинга и масс-спектрометрии позволяют эффективно выявлять гетерогенность гепатоцитов по метаболическому статусу. Наличие гетерогенности необходимо учитывать при анализе ткани печени в различных состояниях с применением методов флуоресцентного биоимиджинга.

  1. Jungermann K. Dynamics of zonal hepatocyte heterogeneity. Perinatal development and adaptive alterations during regeneration after partial hepatectomy, starvation and diabetes. Acta Histochem Suppl 1986; 32: 89–98.
  2. Gebhardt R. Metabolic zonation of the liver: regulation and implications for liver function. Pharmacol Ther 1992; 53(3): 275–354, https://doi.org/10.1016/0163-7258(92)90055-5.
  3. Jungermann K., Kietzmann T. Zonation of parenchymal and nonparenchymal metabolism in liver. Annu Rev Nutr 1996; 16: 179–203, https://doi.org/10.1146/annurev.nu.16.070196.001143.
  4. Kietzmann T. Metabolic zonation of the liver: the oxygen gradient revisited. Redox Biol 2017; 11: 622–630, https://doi.org/10.1016/j.redox.2017.01.012.
  5. Fan T.W.M., Higashi R.M., Chernayavskaya Y., Lane A.N. Resolving metabolic heterogeneity in experimental models of the tumor microenvironment from a stable isotope resolved metabolomics perspective. Metabolites 2020; 10(6): 249, https://doi.org/10.3390/metabo10060249.
  6. Hoover E.E., Squier J.A. Advances in multiphoton microscopy technology. Nat Photonics 2013; 7(2): 93–101, https://doi.org/10.1038/nphoton.2012.361.
  7. Kuimova M.K., Yahioglu G., Levitt J.A., Suhling K. Molecular rotor measures viscosity of live cells via fluorescence lifetime imaging. J Am Chem Soc 2008; 130(21): 6672–6673, https://doi.org/10.1021/ja800570d.
  8. Okabe K., Inada N., Gota C., Harada Y., Funatsu T., Uchiyama S. Intracellular temperature mapping with a fluorescent polymeric thermometer and fluorescence lifetime imaging microscopy. Nat Commun 2012; 3(1): 1–9, https://doi.org/10.1038/ncomms1714.
  9. Suhling K., Siegel J., Phillips D., French P.M., Lévêque-Fort S., Webb S.E., Davis D.M. Imaging the environment of green fluorescent protein. Biophys J 2002; 83(6): 3589–3595, https://doi.org/10.1016/s0006-3495(02)75359-9.
  10. Becker W., Shcheslavkiy V., Frere S., Slutsky I. Spatially resolved recording of transient fluorescence-lifetime effects by line-scanning TCSPC. Microsc Res Tech 2014; 77(3): 216–224, https://doi.org/10.1002/jemt.22331.
  11. Ying W. NAD+/NADH and NADP+/NADPH in cellular functions and cell death: regulation and biological consequences. Antioxid Redox Signal 2008; 10(2): 179–206, https://doi.org/10.1089/ars.2007.1672.
  12. Lakowicz J.R., Szmacinski H., Nowaczyk K., Johnson M.L. Fluorescence lifetime imaging of free and protein-bound NADH. Proc Natl Acad Sci U S A 1992; 89(4): 1271–1275, https://doi.org/10.1073/pnas.89.4.1271.
  13. Heikal A.A. Intracellular coenzymes as natural biomarkers for metabolic activities and mitochondrial anomalies. Biomark Med 2010; 4(2): 241–263, https://doi.org/10.2217/bmm.10.1.
  14. Huang S., Heikal A.A., Webb W.W. Two-photon fluorescence spectroscopy and microscopy of NAD(P)H and flavoprotein. Biophys J 2002; 82(5): 2811–2825, https://doi.org/10.1016/s0006-3495(02)75621-x.
  15. Kolenc O.I., Quinn K.P. Evaluating cell metabolism through autofluorescence imaging of NAD(P)H and FAD. Antioxid Redox Signal 2019; 30(6): 875–889, https://doi.org/10.1089/ars.2017.7451.
  16. Roberts M.S., Dancik Y., Prow T.W., Thorling C.A., Lin L.L., Grice J.E., Robertson T.A., König K., Becker W. Non-invasive imaging of skin physiology and percutaneous penetration using fluorescence spectral and lifetime imaging with multiphoton and confocal microscopy. Eur J Pharm Biopharm 2011; 77(3): 469–488, https://doi.org/10.1016/j.ejpb.2010.12.023.
  17. Stringari C., Nourse J.L., Flanagan L.A., Gratton E. Phasor fluorescence lifetime microscopy of free and protein-bound NADH reveals neural stem cell differentiation potential. PloS One 2012; 7(11): e48014, https://doi.org/10.1371/journal.pone.0048014.
  18. Stringari C., Donovan P., Gratton E. Phasor FLIM metabolic mapping of stem cells and cancer cells in live tissues. In: Proc. SPIE 8226, Multiphoton microscopy in the biomedical sciences XII. SPIE; 2012, https://doi.org/10.1117/12.909420.
  19. Thorling C.A., Liu X., Burczynski F.J., Fletcher L.M., Gobe G., Roberts M.S., Multiphoton microscopy can visualize zonal damage and decreased cellular metabolic activity in hepatic ischemia-reperfusion injury in rats. J Biomed Opt 2011; 16(11): 116011, https://doi.org/10.1117/1.3647597.
  20. Bird D.K., Yan L., Vrotsos K.M., Eliceiri K.W., Vaughan E.M., Keely P.J., White J.G., Ramanujam N. Metabolic mapping of MCF10A human breast cells via multiphoton fluorescence lifetime imaging of the coenzyme NADH. Cancer Res 2005; 65(19): 8766–8773, https://doi.org/10.1158/0008-5472.can-04-3922.
  21. Lakner P.H., Monaghan M.G., Möller Y., Olayioye M.A., Schenke-Layland K. Applying phasor approach analysis of multiphoton FLIM measurements to probe the metabolic activity of three-dimensional in vitro cell culture models. Sci Rep 2017; 7: 42730, https://doi.org/10.1038/srep42730.
  22. Van Nuffel S., Quatredeniers M., Pirkl A., Zakel J., Le Caer J.P., Elie N., Vanbellingen Q.P., Dumas S.J., Nakhleh M.K., Ghigna M.R., Fadel E., Humbert M., Chaurand P., Touboul D., Cohen-Kaminsky S., Brunelle A. Multimodal imaging mass spectrometry to identify markers of pulmonary arterial hypertension in human lung tissue using MALDI-ToF, ToF-SIMS, and hybrid SIMS. Anal Chem 2020; 92(17): 12079–12087, https://doi.org/10.1021/acs.analchem.0c02815.
  23. Gularyan S.K., Gulin A.A., Anufrieva K.S., Shender V.O., Shakhparonov M.I., Bastola S., Antipova N.V., Kovalenko T.F., Rubtsov Y.P., Latyshev Y.A., Potapov A.A., Pavlyukov M.S. Investigation of inter- and intratumoral heterogeneity of glioblastoma using TOF-SIMS. Mol Cell Proteomics 2020; 19(6): 960–970, https://doi.org/10.1074/mcp.ra120.001986.
  24. Petit V.W., Réfrégiers M., Guettier C., Jamme F., Sebanayakam K., Brunelle A., Laprévote O., Dumas P., Le Naour F. Multimodal spectroscopy combining time-of-flight-secondary ion mass spectrometry, synchrotron-FT-IR, and synchrotron-UV microspectroscopies on the same tissue section. Anal Chem 2010; 82(9): 3963–3968, https://doi.org/10.1021/ac100581y.
  25. Debois D., Bralet M.P., Le Naour F., Brunelle A., Laprévote O. In situ lipidomic analysis of nonalcoholic fatty liver by cluster TOF-SIMS imaging. Anal Chem 2009; 81(8): 2823–2831, https://doi.org/10.1021/ac900045m.
  26. Kuznetsova D.S., Rodimova S.A., Gulin A., Reunov D., Bobrov N., Polozova A.V., Vasin A., Shcheslavskiy V.I., Vdovina N., Zagainov V.E., Zagaynova E.V. Metabolic imaging and secondary ion mass spectrometry to define the structure and function of liver with acute and chronic pathology. J Biomed Opt 2019; 25(1): 014508, https://doi.org/10.1117/1.jbo.25.1.014508.
  27. Wang H., Liang X., Gravot G., Thorling C.A., Crawford D.H., Xu Z.P., Liu X., Roberts M.S. Visualizing liver anatomy, physiology and pharmacology using multiphoton microscopy. J Biophotonics 2017; 10(1): 46–60, https://doi.org/10.1002/jbio.201600083.
  28. Rudkouskaya A., Sinsuebphon N., Intes X., Barroso M. Role of tumor heterogeneity in imaging breast cancer targeted delivery using FLIM FRET in vivo. In: Cancer imaging and therapy. OSA; 2016; CTh2A-5, https://doi.org/10.1364/cancer.2016.cth2a.5.
  29. Trinh A.L., Chen H., Chen Y., Hu Y., Li Z., Siegel E.R., Linskey M.E., Wang P.H., Digman M.A., Zhou Y.H. Tracking functional tumor cell subpopulations of malignant glioma by phasor fluorescence lifetime imaging microscopy of NADH. Cancers (Basel) 2017; 9(12): 168, https://doi.org/10.3390/cancers9120168.
  30. Barnes C.A., Brison J., Robinson M., Graham D.J., Castner D.G., Ratner B.D. Identifying individual cell types in heterogeneous cultures using secondary ion mass spectrometry imaging with C60 etching and multivariate analysis. Anal Chem 2012; 84(2): 893–900, https://doi.org/10.1021/ac201179t.
  31. Dimovska Nilsson K., Neittaanmäki N., Zaar O., Angerer T.B., Paoli J., Fletcher J.S. TOF-SIMS imaging reveals tumor heterogeneity and inflammatory response markers in the microenvironment of basal cell carcinoma. Biointerphases 2020; 15(4): 041012, https://doi.org/10.1116/6.0000340.
  32. Клатт Э.К. Атлас патологии Роббинса и Котрана. М: Логосфера; 2010.
  33. Лилли Р. Патогистологическая техника и практическая гистохимия. Пер. В.В. Португалова. М: Мир; 1969.
  34. Ben-Moshe S., Itzkovitz S. Spatial heterogeneity in the mammalian liver. Nat Rev Gastroenterol Hepatol 2019; 16(7): 395–410, https://doi.org/10.1038/s41575-019-0134-x.
  35. Godoy P., Hewitt N.J., Albrecht U., Andersen M.E., Ansari N., Bhattacharya S., Bode J.G., Bolleyn J., Borner C., Böttger J., Braeuning A., Budinsky R.A., Burkhardt B., Cameron N.R., Camussi G., Cho C.S., Choi Y.J., Craig Rowlands J., Dahmen U., Damm G., Dirsch O., Donato M.T., Dong J., Dooley S., Drasdo D., Eakins R., Ferreira K.S., Fonsato V., Fraczek J., Gebhardt R., Gibson A., Glanemann M., Goldring C.E., Gómez-Lechón M.J., Groothuis G.M., Gustavsson L., Guyot C., Hallifax D., Hammad S., Hayward A., Häussinger D., Hellerbrand C., Hewitt P., Hoehme S., Holzhütter H.G., Houston J.B., Hrach J., Ito K., Jaeschke H., Keitel V., Kelm J.M., Kevin Park B., Kordes C., Kullak-Ublick G.A., LeCluyse E.L., Lu P., Luebke-Wheeler J., Lutz A., Maltman D.J., Matz-Soja M., McMullen P., Merfort I., Messner S., Meyer C., Mwinyi J., Naisbitt D.J., Nussler A.K., Olinga P., Pampaloni F., Pi J., Pluta L., Przyborski S.A., Ramachandran A., Rogiers V., Rowe C., Schelcher C., Schmich K., Schwarz M., Singh B., Stelzer E.H., Stieger B., Stöber R., Sugiyama Y., Tetta C., Thasler W.E., Vanhaecke T., Vinken M., Weiss T.S., Widera A., Woods C.G., Xu J.J., Yarborough K.M., Hengstler J.G. Recent advances in 2D and 3D in vitro systems using primary hepatocytes, alternative hepatocyte sources and non-parenchymal liver cells and their use in investigating mechanisms of hepatotoxicity, cell signaling and ADME. Arch Toxicol 2013; 87(8): 1315–1530, https://doi.org/10.1007/s00204-013-1078-5.
  36. Gebhardt R. Matz-Soja M. Liver zonation: novel aspects of its regulation and its impact on homeostasis. World J Gastroenterol 2014; 20(26): 8491–8504, https://doi.org/10.3748/wjg.v20.i26.8491.
  37. Colnot S., Perret C. Liver zonation. In: Molecular pathology of liver diseases. Monga P.S. (editor). Springer; 2011; p. 7–16.
  38. Chen F., Jimenez R.J., Sharma K., Luu H.Y., Hsu B.Y., Ravindranathan A., Stohr B.A., Willenbring H. Broad distribution of hepatocyte proliferation in liver homeostasis and regeneration. Cell Stem Cell 2020; 26(1): 27-33.e4, https://doi.org/10.1016/j.stem.2019.11.001.
  39. Gilgenkrantz H., Collin de l’Hortet A. Understanding liver regeneration: from mechanisms to regenerative medicine. Am J Pathol 2018, 188(6): 1316–1327, https://doi.org/10.1016/j.ajpath.2018.03.008.
  40. Hijmans B.S., Grefhorst A., Oosterveer M.H., Groen A.K. Zonation of glucose and fatty acid metabolism in the liver: mechanism and metabolic consequences. Biochimie 2014, 96: 121–129, https://doi.org/10.1016/j.biochi.2013.06.007.
  41. Guzman M., Castro J. Zonal heterogeneity of the effects of chronic ethanol feeding on hepatic fatty acid metabolism. Hepatology 1990, 12(5): 1098–1105, https://doi.org/10.1002/hep.1840120504.
  42. Tessari P., Coracina A., Cosma A., Tiengo A. Hepatic lipid metabolism and non-alcoholic fatty liver disease. Nutr Metab Cardiovasc Dis 2009, 19(4): 291–302, https://doi.org/10.1016/j.numecd.2008.12.015.
  43. Soto-Gutierrez A., Gough A., Vernetti L.A., Taylor D.L., Monga S.P. Pre-clinical and clinical investigations of metabolic zonation in liver diseases: the potential of microphysiology systems. Exp Biol Med (Maywood) 2017; 242(16): 1605–1616, https://doi.org/10.1177/1535370217707731.
  44. Shaw S. Lipid peroxidation, iron mobilization and radical generation induced by alcohol. Free Radic Biol Med 1989, 7(5): 541–547, https://doi.org/10.1016/0891-5849(89)90030-0.
  45. Skala M.C., Riching K.M., Gendron-Fitzpatrick A., Eickhoff J., Eliceiri K.W., White J.G., Ramanujam N. In vivo multiphoton microscopy of NADH and FAD redox states, fluorescence lifetimes, and cellular morphology in precancerous epithelia. Proc Natl Acad Sci U S A 2007; 104(49): 19494–19499, https://doi.org/10.1073/pnas.0708425104.
  46. Lukina M., Shirmanova M., Dudenkova V., Druzhkova I., Shumilova A., Zagaynova E. Analysis of energy metabolism of HeLa cancer cells in vitro and in vivo using fluorescence lifetime microscopy. In: Proc. SPIE 9887, Biophotonics: photonic solutions for better health care V. SPIE; 2016, https://doi.org/10.1117/12.2227488.
  47. Shirmanova M.V., Lukina M.M., Lyubov’ E.S., Kuimova M.K., Dudenkova V.V., Shcheslavskiy V.I., Zagaynova E.V. Probing energy metabolism and microviscosity in cancer using FLIM. In: Proc. SPIE 10411, Clinical and preclinical optical diagnostics. SPIE; 2017, https://doi.org/10.1117/12.2287094.
  48. Varum S., Rodrigues A.S., Moura M.B., Momcilovic O., Easley C.A. IV, Ramalho-Santos J., Van Houten B., Schatten G. Energy metabolism in human pluripotent stem cells and their differentiated counterparts. PloS One 2011, 6(6): e20914, https://doi.org/10.1371/journal.pone.0020914.
  49. Folmes C.D., Nelson T.J., Martinez-Fernandez A., Arrell D.K., Lindor J.Z., Dzeja P.P., Ikeda Y., Perez-Terzic C., Terzic A. Somatic oxidative bioenergetics transitions into pluripotency-dependent glycolysis to facilitate nuclear reprogramming. Cell Metab 2011; 14(2): 264–271, https://doi.org/10.1016/j.cmet.2011.06.011.
  50. Meleshina A.V., Dudenkova V.V., Bystrova A.S., Kuznetsova D.S., Shirmanova M.V., Zagaynova E.V. Two-photon FLIM of NAD(P)H and FAD in mesenchymal stem cells undergoing either osteogenic or chondrogenic differentiation. Stem Cell Res Ther 2017; 8(1): 15, https://doi.org/10.1186/s13287-017-0484-7.
  51. Lindros K.O., Penttilä K.E. Digitonin-collagenase perfusion for efficient separation of periportal or perivenous hepatocytes. Biochem J 1985; 228(3): 757–760, https://doi.org/10.1042/bj2280757.
  52. Quistorff B. Gluconeogenesis in periportal and perivenous hepatocytes of rat liver, isolated by a new high-yield digitonin/collagenase perfusion technique. Biochem J 1985; 229(1): 221–226, https://doi.org/10.1042/bj2290221.
  53. Katz N.R., Fischer W., Giffhorn S. Distribution of enzymes of fatty acid and ketone body metabolism in periportal and perivenous rat-liver tissue. Eur J Biochem 1983; 135(1): 103–107, https://doi.org/10.1111/j.1432-1033.1983.tb07623.x.
  54. Guzmán M., Castro J. Zonation of fatty acid metabolism in rat liver. Biochem J 1989; 264(1): 107–113, https://doi.org/10.1042/bj2640107.
  55. Guzmán M., Bijleveld C., Geelen M.J.H. Flexibility of zonation of fatty acid oxidation in rat liver. Biochem J 1995; 311(3): 853–860, https://doi.org/10.1042/bj3110853.
Rodimova S.A., Kuznetsova D.S., Bobrov N.V., Gulin A.A., Vasin A.A., Gubina M.V., Scheslavsky V.I., Elagin V.V., Karabut M.M., Zagainov V.E., Zagaynova E.V. Multiphoton Microscopy and Mass Spectrometry for Revealing Metabolic Heterogeneity of Hepatocytes in vivo. Sovremennye tehnologii v medicine 2021; 13(2): 18, https://doi.org/10.17691/stm2021.13.2.02


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