Modern Methods of Fluorescence Nanoscopy in Biology

封面

如何引用文章

全文:

开放存取 开放存取
受限制的访问 ##reader.subscriptionAccessGranted##
受限制的访问 订阅存取

详细

Optical microscopy has undergone significant changes in recent decades due to the breaking of the diffraction limit of optical resolution and the development of high-resolution imaging techniques, which are collectively known as fluorescence nanoscopy. These techniques allow researchers to observe biological structures and processes at a nanoscale level of detail, revealing previously hidden features and aiding in answering fundamental biological questions. Among the advanced methods of fluorescent nanoscopy are: STED (Stimulated Emission Depletion Microscopy), STORM (STochastic Optical Reconstruction Microscopy), PALM (Photo-activated Localization Microscopy), TIRF (Total Internal Reflection Fluorescence), SIM (Structured Illumination Microscopy), MINFLUX (Minimal Photon Fluxes), PAINT (Points Accumulation for Imaging in Nanoscale Topography) и RESOLFT (REversible Saturable Optical Fluorescence Transitions) and others. In addition, most of these methods make it possible to obtain volumetric (3D) images of the objects under study. In this review, we will look at the principles of these methods, their advantages and disadvantages, and their application in biological researches.

全文:

受限制的访问

作者简介

D. Solovyeva

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry

编辑信件的主要联系方式.
Email: d.solovieva@mail.ru
俄罗斯联邦, ul. Miklukho-Maklaya 16/10, Moscow, 117997

A. Altunina

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry; Moscow Institute of Physics and Technology (National Research University)

Email: d.solovieva@mail.ru
俄罗斯联邦, ul. Miklukho-Maklaya 16/10, Moscow, 117997; Institutskiy per. 9, Dolgoprudny, 141701

M. Tretyak

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry

Email: d.solovieva@mail.ru
俄罗斯联邦, ul. Miklukho-Maklaya 16/10, Moscow, 117997

K. Mochalov

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry

Email: d.solovieva@mail.ru
俄罗斯联邦, ul. Miklukho-Maklaya 16/10, Moscow, 117997

V. Oleinikov

Shemyakin–Ovchinnikov Institute of Bioorganic Chemistry; National Research Nuclear University “MEPhI”

Email: d.solovieva@mail.ru
俄罗斯联邦, ul. Miklukho-Maklaya 16/10, Moscow, 117997; Kashirskoye sh. 31, Moscow, 115409

参考

  1. Abbe E. // Archiv für mikroskopische Anatomie. 1873. V. 9. P. 413–468. https://doi.org/10.1007/BF02956173
  2. Minsky M. // Scanning. 1988. V. 10. P. 128–138. https://doi.org/10.1002/sca.4950100403
  3. Kaiser W., Garrett C. // Phys. Rev. Lett. 1961. V. 7. P. 229–231. https://doi.org/10.1103/PhysRevLett.7.229
  4. Hell S.W., Stelzer E.H.K., Lindek S., Cremer C. // Opt. Lett. 1994. V. 19. P. 222–224. https://doi.org/10.1364/OL.19.000222
  5. Bahlmann K., Jakobs S., Hell S.W. // Ultramicroscopy. 2001. V. 87. P. 155–164. https://doi.org/10.1016/S0304-3991(00)00092-9
  6. Khater I.M., Nabi I.R., Hamarneh G. // Patterns. 2020. V. 1. P. 100038. https://doi.org/10.1016/j.patter.2020.100038
  7. Gong J., Jin Z., Chen H., He J., Zhang Y., Yang X. // Adv. Drug Deliv. Rev. 2023. V. 196. P. 114791. https://doi.org/10.1016/j.addr.2023.114791
  8. Werner C., Sauer M., Geis C. // Chem. Rev. 2021. V. 121. P. 11971–12015. https://doi.org/10.1021/acs.chemrev.0c01174
  9. Jacquemet G., Carisey A.F., Hamidi H., Henriques R., Leterrier C. // J. Cell Sci. 2020. V. 133. P. jcs240713. https://doi.org/10.1242/jcs.240713
  10. Vicidomini G., Bianchini P., Diaspro A. // Nat. Methods. 2018. V. 15. P. 173–182. https://doi.org/10.1038/nmeth.4593
  11. Hell S.W., Wichmann J. // Opt. Lett. 1994. V. 19. P. 780–782. https://doi.org/10.1364/ol.19.000780
  12. Hell S.W., Kroug M. // Appl. Phys. B. 1995. V. 60. P. 495–497. https://doi.org/10.1007/BF01081333
  13. Mochalov K.E., Chistyakov A.A., Solovyeva D.O., Mezin A.V., Oleinikov V.A., Vaskan I.S., Molinari M., Agapov I.I., Nabiev I., Efimov A.E. // Ultramicroscopy. 2017. V. 182. P. 118–123. https://doi.org/10.1016/j.ultramic.2017.06.022
  14. Heine J., Wurm C.A., Keller-Findeisen J., Schönle A., Harke B., Reuss M., Winter F.R., Donnert G. // Rev. Sci. Instrum. 2018. V. 89. P. 053701. https://doi.org/10.1063/1.5020249
  15. Blom H., Widengren J. // Curr. Opin. Chem. Biol. 2014. V. 20. P. 127–133. https://doi.org/10.1016/j.cbpa.2014.06.004
  16. Berning S., Willig K.I., Steffens H., Dibaj P., Hell S.W. // Science. 2012. V. 335. P. 551–552. https://doi.org/10.1126/science.1215369
  17. Masch J.-M., Steffens H., Fischer J., Engelhardt J., Hubrich J., Keller-Findeisen J., D’Este E., Urban N.T., Grant S.G.N., Sahl S.J., Kamin D., Hell S.W. // Proc. Natl. Acad. Sci. USA. 2018. V. 115. P. E8047–E8056. https://doi.org/10.1073/pnas.1807104115
  18. Pfeiffer T., Poll S., Bancelin S., Angibaud J., Inavalli V.K., Keppler K., Mittag M., Fuhrmann M., Nägerl U.V. // Elife. 2018. V. 7. P. 1–17. https://doi.org/10.7554/eLife.34700
  19. Steffens H., Wegner W., Willig K.I. // Methods. 2020. V. 174. P. 42–48. https://doi.org/10.1016/j.ymeth.2019.05.020
  20. Calovi S., Soria F.N., Tønnesen J. // Neurobiol. Dis. 2021. V. 156. P. 105420. https://doi.org/10.1016/j.nbd.2021.105420
  21. Katsube S., Koganezawa N., Hanamura K., Cuthill K.J., Tarabykin V., Ambrozkiewicz M.C., Kawabe H. // Neurosci. Lett. 2023. V. 797. P. 137059. https://doi.org/10.1016/j.neulet.2023.137059
  22. Scharrig E., Sanmillan M.L., Giraudo C.G. // Methods Cell Biol. 2023. https://doi.org/10.1016/bs.mcb.2023.01.018
  23. Carravilla P., Dasgupta A., Zhurgenbayeva G., Danylchuk D.I., Klymchenko A.S., Sezgin E., Eggeling C. // Biophys. Rep. 2021. V. 1. P. 100023. https://doi.org/10.1016/j.bpr.2021.100023
  24. Spahn C., Grimm J.B., Lavis L.D., Lampe M., Heilemann M. // Nano Lett. 2019. V. 19. P. 500–505. https://doi.org/10.1021/acs.nanolett.8b04385
  25. Sauer M., Heilemann M. // Chem. Rev. 2017. V. 117. P. 7478–7509. https://doi.org/10.1021/acs.chemrev.6b00667
  26. Keller J., Schönle A., Hell S.W. // Opt. Express. 2007. V. 15. P. 3361–3371. https://doi.org/10.1364/oe.15.003361
  27. Rittweger E., Rankin B.R., Westphal V., Hell S.W. // Chem. Phys. Lett. 2007. V. 442. P. 483–487. https://doi.org/10.1016/j.cplett.2007.06.017
  28. Sharma R., Singh M., Sharma R. // Spectrochim. Acta A Mol. Biomol. Spectrosc. 2020. V. 231. P. 117715. https://doi.org/10.1016/j.saa.2019.117715
  29. Zhang P., Goodwin P.M., Werner J.H. // Opt. Express. 2014. V. 22. P. 12398–12409. https://doi.org/10.1364/OE.22.012398
  30. Yu W., Ji1 Z., Dong D., Yang X., Xiao Y., Gong Q., Xi P., Shi K. // Laser Photonics Rev. 2016. V. 10. P. 147–152. https://doi.org/10.1002/lpor.201500151
  31. Frawley A.T., Wycisk V., Xiong Y., Galiani S., Sezgin E., Urbančič I., Jentzsch A.V., Leslie K.G., Eggeling C., Anderson H.L. // Chem. Sci. 2020. V. 11. P. 8955–8960. https://doi.org/10.1039/D0SC02447C
  32. Damenti M., Coceano G., Pennacchietti F., Bodén A., Testa I. // Neurobiol. Dis. 2021. V. 155. P. 105361. https://doi.org/10.1016/j.nbd.2021.105361
  33. Sahl, S.J., Hell, S.W. // In: High Resolution Imaging in Microscopy and Ophthalmology / Eds. Bille J. Cham: Springer, 2019. P. 3–32. https://doi.org/10.1007/978-3-030-16638-0_1
  34. Boden A., Pennacchietti F., Coceano G., Damenti M., Ratz M., Testa I. // Nat. Biotechnol. 2021. V. 39. P. 609–618. https://doi.org/10.1038/s41587-020-00779-2
  35. Willig K.I. // iScience. 2022. V. 25. P. 104961. https://doi.org/10.1016/j.isci.2022.104961
  36. Rust M.J., Bates M., Zhuang X.W. // Nat. Methods. 2006. V. 3. P. 793–795. https://doi.org/10.1038/nmeth929
  37. Hess S.T., Girirajan T.P.K., Mason M.D. // Biophys. J. 2006. V. 91. V. 4258–4272. https://doi.org/10.1529/biophysj.106.091116
  38. Kikuchi K., Adair L.D., Lin J., New E.J., Kaur A. // Angew. Chem. Int. Ed. Engl. 2023. V. 62. P. e202204745. https://doi.org/10.1002/anie.202204745
  39. Li H., Vaughan J.C. // Chem. Rev. 2018. V. 118. P. 9412–9454. https://doi.org/10.1021/acs.chemrev.7b00767
  40. Huang B., Wang W., Bates M., Zhuang X. // Science. 2008. V. 319. P. 810–813. https://doi.org/10.1126/science.1153529
  41. Albrecht N.E., Jiang D., Akhanov V., Hobson R., Speer C.M., Robichaux M.A., Samuel M.A. // Cell Rep. Methods. 2022. V. 2. P. 100253. https://doi.org/10.1016/j.crmeth.2022.100253
  42. Hu F., Zhu D., Dong H., Zhang P., Xing F., Li W., Yan R., Zhou J., Xu K., Pan L., Xu J. // iScience. 2022. V. 25. P. 105514. https://doi.org/10.1016/j.isci.2022.105514
  43. Kim D., Deerinck T.J., Sigal Y.M., Babcock H.P., Ellisman M.H., Zhuang X. // PLoS One. 2015. V. 10. P. e0124581. https://doi.org/10.1371/journal.pone.0124581
  44. Betzig E., Patterson G.H., Sougrat R., Lindwasser O.W., Olenych S., Bonifacino J.S., Davidson M.W., Lippincott-Schwartz J., Hess H.F. // Science. 2006. V. 313. P. 1642–1645. https://doi.org/10.1126/science.1127344
  45. Shtengel G., Galbraith J.A., Galbraith C.G., Lippincott-Schwartz J., Gillette J.M., Manley S., Sougrat R., Waterman C.M., Kanchanawong P., Davidson M.W., Fetter R.D., Hess H.F. // PNAS. 2009. V. 106. P. 3125–3130. https://doi.org/10.1073/pnas.0813131106
  46. Shtengel G., Wang Y., Zhang Z., Goh W.I., Hess H.F., Kanchanawong P. // Methods Cell Biol. 2014. V. 123. P. 273–294. https://doi.org/10.1016/B978-0-12-420138-5.00015-X
  47. Baddeley D., Bewersdorf J. // Annu. Rev. Biochem. 2018. V. 87. P. 965–989. https://doi.org/10.1146/annurev-biochem-060815-014801
  48. Lemcke H., Skorska A., Lang C.I., Johann L., David R. // Int. J. Mol. Sci. 2020. V. 21. P. 2819. https://doi.org/10.3390/ijms21082819
  49. Saha I., Saffarian S. // Biophys. J. 2020. V. 119. P. 581–592. https://doi.org/10.1016/j.bpj.2020.06.023
  50. Chojnacki J., Eggeling C. // Retrovirology. 2018. V. 15. P. 41. https://doi.org/10.1186/s12977-018-0424-3
  51. Herron J.C., Hu S., Watanabe T., Nogueira A.T., Liu B., Kern M.E., Aaron J., Taylor A., Pablo M., Chew T.L., Elston T.C., Hahn K.M. // Nat. Commun. 2022. V. 13. P. 4363. https://doi.org/10.1038/s41467-022-32038-0
  52. Parteka-Tojek Z., Zhu J.J., Lee B., Jodkowska K., Wang P., Aaron J., Chew T.L., Banecki K., Plewczynski D., Ruan Y. // Sci. Rep. 2022. V. 12. P. 8582. https://doi.org/10.1038/s41598-022-12568-9
  53. Trzaskoma P., Ruszczycki B., Lee B., Pels K.K., Krawczyk K., Bokota G., Szczepankiewicz A.A., Aaron J., Walczak A., Śliwińska M.A., Magalska A., Kadlof M., Wolny A., Parteka Z., Arabasz S., KissArabasz M., Plewczyński D., Ruan Y., Wilczyński G.M. // Nat. Commun. 2020. V. 11. P. 2120. https://doi.org/10.1038/s41467-020-15987-2
  54. Sharonov A., Hochstrasser R.M. // Proc. Natl. Acad. Sci. USA. 2006. V. 103. P. 18911–18916. https://doi.org/10.1073/pnas.0609643104
  55. Schnitzbauer J., Strauss M., Schlichthaerle T., Schueder F., Jungmann R. // Nat. Protoc. 2017. V. 12. P. 1198–1228. https://doi.org/10.1038/nprot.2017.024
  56. Jungmann R., Avendano M.S., Woehrstein J.B., Dai M., Shih W.M., Yin P. // Nat. Methods. 2014. V. 11. P. 313–318. https://doi.org/10.1038/nmeth.2835
  57. Niederauer C., Nguyen C., Wang-Henderson M., Stein J., Strauss S., Cumberworth A., Stehr F., Jungmann R., Schwille P., Ganzinger K.A. // Nat. Commun. 2023. V. 14. P. 4345. https://doi.org/10.1038/s41467-023-40065-8
  58. Brockman J.M., Su H., Blanchard A.T., Duan Y., Meyer T., Quach M.E., Glazier R., Bazrafshan A., Bender R.L., Kellner A.V., Ogasawara H., Ma R., Schueder F., Petrich B.G., Jungmann R., Li R., Mattheyses A.L., Ke Y., Salaita K. // Nat. Methods. 2020. V. 17. P. 1018–1024. https://doi.org/10.1038/s41592-020-0929-2
  59. Tholen M.M.E., Tas R.P., Wang Y., Albertazzi L. // Chem. Commun. (Camb). 2023. V. 59. P. 8332– 8342. https://doi.org/10.1039/d3cc00757j
  60. Chang Y., Kim D.H., Zhou K., Jeong M.G., Park S., Kwon Y., Hong T.M., Noh J., Ryu S.H. // Exp. Mol. Med. 2021. V. 53. P. 384–392. https://doi.org/10.1038/s12276-021-00572-4
  61. Riera R., Hogervorst T.P., Doelman W., Ni Y., Pujals S., Bolli E., Codée J.D.C., van Kasteren S.I., Albertazzi L. // Nat. Chem. Biol. 2021. V. 17. P. 1281–1288. https://doi.org/10.1038/s41589-021-00896-2
  62. Farrell M.V., Nunez A.C., Yang Z., Pérez-Ferreros P., Gaus K., Goyette J. // Sci. Signal. 2022. V. 15. P. eabg9782. https://doi.org/10.1126/scisignal.abg9782
  63. Oi C., Gidden Z., Holyoake L., Kantelberg O., Mochrie S., Horrocks M.H., Regan L. // Commun. Biol. 2020. V. 3. P. 458. https://doi.org/10.1038/s42003-020-01188-6
  64. Gwosch K.C., Pape J.K., Balzarotti F., Hoess P., Ellenberg J., Ries J., Hell S.W. // Nat. Methods. 2020. V. 17. P. 217–224. https://doi.org/10.1038/s41592-019-0688-0
  65. Balzarotti F., Eilers Y., Gwosch K.C., Gynnå A.H., Westphal V., Stefani F.D., Elf J., Hell S.W. // Science. 2017. V. 355. P. 606–612. https://doi.org/10.1126/science.aak9913
  66. Prakash K., Curd A.P. // Nat. Methods. 2023. V. 20. P. 48–51. https://doi.org/10.1038/s41592-022-01694-x
  67. Gwosch K.C., Balzarotti F., Pape J.K., Hoess P., Ellenberg J., Ries J., Matti U., Schmidt R., Sahl S.J., Hell S.W. // Nat. Methods. 2023. V. 20. P. 52–54. https://doi.org/10.1038/s41592-022-01695-w
  68. Wolff J.O., Scheiderer L., Engelhardt T., Engelhardt J., Matthias J., Hell S.W. // Science. 2023. V. 379. P. 1004–1010. https://doi.org/10.1126/science.ade2650
  69. Deguchi T., Iwanski M.K., Schentarra E.M., Heidebrecht C., Schmidt L., Heck J., Weihs T., Schnorrenberg S., Hoess P., Liu S., Chevyreva V., Noh K.M., Kapitein L.C., Ries J. // Science. 2023. V. 379. P. 1010–1015. https://doi.org/10.1126/science.ade2676
  70. Ostersehlt L.M., Jans D.C., Wittek A., KellerFindeisen J., Inamdar K., Sahl S.J., Hell S.W., Jakobs S. // Nat. Methods. 2022. V. 19. P. 1072–1075. https://doi.org/10.1038/s41592-022-01577-1
  71. Mulhall E.M., Gharpure A., Lee R.M., Dubin A.E., Aaron J.S., Marshall K.L., Spencer K.R., Reiche M.A., Henderson S.C., Chew T.L., Patapoutian A. // Nature. 2023. V. 620. P. 1117–1125. https://doi.org/10.1038/s41586-023-06427-4.
  72. Carsten A., Rudolph M., Weihs T., Schmidt R., Jansen I., Wurm C.A., Diepold A., Failla A.V., Wolters M., Aepfelbacher M. // Methods Appl. Fluoresc. 2022. V. 11. https://doi.org/10.1088/2050-6120/aca880
  73. Pape J.K., Stephan T., Balzarotti F., Büchner R., Lange F., Riedel D., Jakobs S., Hell S.W. // Proc. Natl. Acad. Sci. USA. 2020. V. 117. P. 20607–20614. https://doi.org/10.1073/pnas.2009364117
  74. Gustafsson M.G.L. // J. Microsc. 2000. V. 198. P. 82–87. https://doi.org/10.1046/j.1365-2818.2000.00710.x
  75. Gustafsson M.G.L., Shao L., Carlton P.M., Wang C.J.R., Golubovskaya I.N., Cande W.Z, Agard D.A., Sedat J.W. // Biophys. J. 2008. V. 94. P. 4957–4970. https://doi.org/10.1529/biophysj.107.120345
  76. Manton J.D. // Philos. Trans. A Math. Phys. Eng. Sci. 2022. V. 380. P. 20210109. https://doi.org/10.1098/rsta.2021.0109
  77. Zhao T., Wang Z., Chen T., Lei M., Yao B., Bianco P.R. // Front. Phys. 2021. V. 9. P. 672555. https://doi.org/10.3389/fphy.2021.672555
  78. Chen X., Zhong S., Hou Y., Cao R., Wang W., Li D., Dai Q., Kim D., Xi P. // Light Sci. Appl. 2023. V. 12. P. 172. https://doi.org/10.1038/s41377-023-01204-4
  79. Wang M., Chen J., Wang L., Zheng X., Zhou J., Zeng Y., Qu J., Shao Y., Gao B.Z. // Chemosensors. 2021. V. 9. P. 364. https://doi.org/10.3390/chemosensors9120364
  80. Hamel V., Guichard P., Fournier M., Guiet R., Fluckiger I., Seitz A., Gonczy P. // Biomed. Opt. Express. 2014. V. 5. P. 3326–3336. https://doi.org/10.1364/BOE.5.003326
  81. Dake F. // Opt. Rev. 2016. V. 23. P. 587–595. https://doi.org/10.1007/s10043-016-0234-6
  82. Xue Y., So P.T.C. // Opt. Express. 2018. V. 26. P. 20920– 20928. https://doi.org/10.1364/OE.26.020920
  83. Fiolka R., Beck M., Stemmer A. // Opt. Lett. 2008. V. 33. P. 1629–1631. https://doi.org/10.1364/OL.33.001629
  84. Roth J., Mehl J., Rohrbach A. // Biomed. Opt. Express. 2020. V. 11. P. 4008–4026. https://doi.org/10.1364/BOE.391561
  85. Hinsdale T.A., Stallinga S., Rieger B. // Biomed. Opt. Express. 2021. V. 12. P. 1181–1194. https://doi.org/10.1364/BOE.416546
  86. Heintzmann R., Huser T. // Chem. Rev. 2017. V. 117. P. 13890–13908. https://doi.org/10.1021/acs.chemrev.7b00218
  87. Ward E.N., Hecker L., Christensen C.N., Lamb J.R., Lu M., Mascheroni L., Chung C.W., Wang A., Rowlands C.J., Schierle G.S.K., Kaminski C.F. // Nat. Commun. 2022. V. 13. P. 7836. https://doi.org/10.1038/s41467-022-35307-0
  88. Mennella V. // In: Encyclopedia of Cell Biology (Second Edition) / Eds. Ralph A., Hart B.G.W., Stahl P.D. Academic Press, 2023. P. 105–121. https://doi.org/10.1016/B978-0-12-821618-7.00116-4
  89. Hong S., Wilton D.K., Stevens B., Richardson D.S. // Methods Mol. Biol. 2017. V. 1538. P. 155–167. https://doi.org/10.1007/978-1-4939-6688-2_12
  90. Sulkowski M.J., Han T.H., Ott C., Wang Q., Verheyen E.M., Lippincott-Schwartz J., Serpe M. // PLoS Genet. 2016. V. 12. P. e1005810. https://doi.org/10.1371/journal.pgen.1005810
  91. Badawi Y., Nishimune H. // Neurosci. Lett. 2020. V. 715. P. 134644. https://doi.org/10.1016/j.neulet.2019.134644
  92. Miao L., Yan C., Chen Y., Zhou W., Zhou X., Qiao Q., Xu Z. // Cell Chem. Biol. 2023. V. 30. P. 248–260. https://doi.org/10.1016/j.chembiol.2023.02.001
  93. Mudry E., Belkebir K., Girard J., Savatier J., Le Moal E., Nicoletti C., Allain M., Sentenac A. // Nat. Photon. 2012. V. 6. P. 312–315. https://doi.org/10.1038/nphoton.2012.83
  94. Mangeat T., Labouesse S., Allain M., Negash A., Martin E., Guénolé A., Poincloux R., Estibal C., Bouissou A., Cantaloube S., Vega E., Li T., Rouvière C., Allart S., Keller D., Debarnot V., Wang X.B., Michaux G., Pinot M., Le Borgne R., Tournier S., Suzanne M., Idier J., Sentenac A. // Cell Rep. Methods. 2021. V. 1. P. 100009. https://doi.org/10.1016/j.crmeth.2021.100009
  95. Labouesse S., Idier J., Sentenac A., Mangeat T., Allain M. // Random Illumination Microscopy from Variance Images / 28th European Signal Processing Conference (EUSIPCO), Amsterdam, Netherlands, 2021. P. 785–789. https://doi.org/10.23919/Eusipco47968.2020.9287651
  96. Liu P. // Appl. Opt. 2022. V. 61. P. 2910–2914. https://doi.org/10.1364/AO.452709
  97. Affannoukoué K., Labouesse S., Maire G., Gallais L., Savatier J., Allain M., Rasedujjaman M., Legoff L., Idier J., Poincloux R., Pelletier F., Leterrier C., Mangeat T., Sentenac A. // Optica. 2023. V. 10. P. 1009–1017. https://doi.org/10.1364/OPTICA.487003
  98. Axelrod D. // Traffic. 2001. V. 2. P. 764–774. https://doi.org/10.1034/j.1600-0854.2001.21104.x
  99. Janco M., Dedova I., Bryce N.S., Hardeman E.C., Gunning P.W. // Biophys. Rev. 2020. V. 12. P. 879– 885. https://doi.org/10.1007/s12551-020-00720-6
  100. Shen H., Huang E., Das T., Xu H., Ellisman M., Liu Z. // Opt. Express. 2014. V. 22. P. 10728–10734. https://doi.org/10.1364/OE.22.010728
  101. Fish K.N. // Curr. Protoc. Cytom. 2009. V. 12. P. Unit12.18. https://doi.org/10.1002/0471142956.cy1218s50
  102. McCluskey K., Dekker N.H. // Opt. Commun. 2023. V. 538. P. 129474. https://doi.org/10.1016/j.optcom.2023.129474
  103. Fan D., Cnossen J., Hung S.-T., Kromm D., Dekker N.H., Verbiest G.J., Smith G.S. // Opt. Commun. 2023. V. 542. P. 129548. https://doi.org/10.1016/j.optcom.2023.129548
  104. Soubies E., Radwanska A., Grall D., Blanc-Féraud L., Van Obberghen-Schilling E., Schaub S. // Sci. Rep. 2019. V. 9. P. 1926. https://doi.org/10.1038/s41598-018-36119-3
  105. Jung Y., Riven I., Feigelson S.W., Kartvelishvily E., Tohya K., Miyasaka M., Alon R., Haran G. // Proc. Natl. Acad. Sci. USA. 2016. V. 113. P. E5916–E5924. https://doi.org/10.1073/pnas.1605399113
  106. Szalai A.M., Siarry B., Lukin J., Williamson D.J., Unsain N., Cáceres A., Pilo-Pais M., Acuna G., Refojo D., Owen D.M., Simoncelli S., Stefani F.D. // Nat. Commun. 2021. V. 12. P. 517. https://doi.org/10.1038/s41467-020-20863-0
  107. Young L.J., Ströhl F., Kaminski C.F.A. // J. Vis. Exp. 2016. V. 111. P. e53988. https://doi.org/10.3791/53988
  108. Opstad I.S., Ströhl F., Fantham M., Hockings C., Vanderpoorten O., van Tartwijk F.W., Lin J.Q., Tinguely J.-C., Dullo F.T., Kaminski-Schierle G.S., Ahluwalia B.S., Kaminski C.F. // J. Biophotonics. 2020. V. 13. P. e201960222. https://doi.org/10.1002/jbio.201960222
  109. Villegas-Hernández L.E., Dubey V., Nystad M., Tinguely J.-C., Coucheron D.A., Dullo F.T., Priyadarshi A., Acuña S., Ahmad A., Mateos J.M., Barmettler G., Ziegler U., Birgisdottir Å.B., Karlsson Hovd A.-M., Fenton K.A., Acharya G., Agarwal K., Ahluwalia B.S. // Light Sci. Appl. 2022. V. 11. P. 43. https://doi.org/10.1038/s41377-022-00731-w

补充文件

附件文件
动作
1. JATS XML
下载
2. Fig. 1. Schematic diagram showing the resolution of a light optical microscope.

下载 (176KB)
索引源数据
3. Fig. 2. Classification of super-resolution microscopy methods. (a), (b) – Deterministic methods based on information about the spatial distribution: (a) – embedded in the illumination pattern (sequential illumination of the sample by a standing wave): SIM (Structured Illumination Microscopy), SMI (Spatially Modulated Illumination Microscopy), SSIM (Saturated Structured Illumination Microscopy); (b) – about the size of the light-emitting region (the response of the fluorophore to light excitation that stimulates emission): RESOLFT (REversible Saturable Optical Fluorescence Transitions), STED (Stimulated Emission Depletion Microscopy), SPEM (Scanning PhotoElectron Microscope), GSD (Ground State Depletion Microscopy), TIRF (Total Internal Reflection Fluorescence); (c) – stochastic methods based on the ability to localize single molecules with virtually any accuracy, which is determined by the number of registered photons: PAINT (Points Accumulation for Imaging in Nanoscale Topography), DNA-PAINT (DNA Points Accumulation for Imaging in Nanoscale Topography), STORM (STochastic Optical Reconstruction Microscopy), dSTORM (Direct Stochastic Optical Reconstruction Microscopy), PALM (Photo-activated Localization Microscopy), fPALM (DNA structure fluctuation-assisted BALM), BALM (Binding-Activated Localization Microscopy), MINFLUX (Minimal Photon Fluxes), SOFI (Super-resolution Optical Fluctuation Imaging).

下载 (423KB)
索引源数据
4. Fig. 3. 3D-STED imaging of fixed HeLa cells with fluorescently labeled membranes (green) and DNA (red), achieving near isotropic resolution, scale bar 5 μm [24].

下载 (421KB)
索引源数据
5. Fig. 4. STORM imaging sequence using a hypothetical hexameric object labeled with red fluorophores that can be switched between fluorescent and dark states using red and green lasers. All fluorophores are first switched to the dark state by a red laser pulse. In each imaging cycle, a green laser pulse is used to turn on only a subset of the fluorophores, forming an optically resolved set of active fluorophores. These molecules then emit fluorescence under red illumination until they are switched off, allowing their positions to be determined with high precision (white crosses). The overall image is then reconstructed based on the fluorophore positions obtained from multiple imaging cycles [36].

下载 (143KB)
索引源数据
6. Fig. 5. (a) Unoptimized STORM image of a horizontal cell labeled with calbindin. Putative synapses are unclear, with little defining morphology or continuous structure (unoptimized inset); (b) under optimized RAIN-STORM conditions, both the cells’ horizontal synapses and their connecting structures are labeled and juxtaposed (optimized inset), revealing clear structural detail throughout the neuronal arbor. Images are representative of n = 3 animals. STORM images are color-coded by depth (purple = 0 μm to yellow = 10 μm). Scale bars are 10 and 1 μm [41].

下载 (386KB)
索引源数据
7. Fig. 6. Effects of inhibition of Rho/ROCK-myosin IIA signaling on nocodazole-induced podosome cluster disassembly. Representative two-color STORM results of actin and myosin IIA in individual macrophages cultured for 16 h and then treated with Noc (10 μM), Noc (10 μM) + Y27632 (20 μM), and Noc (10 μM) + Bleb (20 μM) for 2 h. Shown are individual images of actin (purple) and myosin IIA (green) as well as an overlay image, respectively.

下载 (261KB)
索引源数据
8. Fig. 7. MINFLUX nanoscopy of U-2 OS cells expressing Nup96, a nuclear pore complex (NPC) protein, labeled with the organic fluorophore Alexa Fluor 647 (top). Magnified sections (bottom) show individual nuclear pores, where each dot highlights groups of localizations representing individual proteins via their fluorescent labels. Scale bars: 500 nm (top), 50 nm (insets) [64].

下载 (160KB)
索引源数据
9. Fig. 8. Capabilities of multicolor high-speed SIM. Field of view 33 × 33 μm, microtubules are shown in red, mitochondria in green. Scale bar 5 μm [85].

下载 (205KB)
索引源数据
10. Fig. 9. 3D-SIM and enlarged 2D/3D image of living HeLa cells incubated with 25 nM h-RBD-SiR for 10 h. Scale bar 2 μm [92].

下载 (271KB)
索引源数据
11. Fig. 10. Localization of L-selectin and CD44 on the 3D surface topography of T cells. (a) 3D reconstruction of the resting membrane surface of human T cells using MA-TIRFM; (b) localization map of L-selectin molecules (orange dots) superimposed on the 3D surface reconstruction map from panel (a). Scale bar 0.5 μm [105].

下载 (246KB)
索引源数据

版权所有 © Russian Academy of Sciences, 2024