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Fluorescence Self-Quenching from Reporter Dyes Informs on the Structural Properties of Amyloid Clusters Formed in Vitro and in Cells

Chen, WeiYue, Young, Laurence J., Lu, Meng, Zaccone, Alessio, Ströhl, Florian, Yu, Na, Kaminski Schierle, Gabriele S., Kaminski, Clemens F.·2017·Nano Letters

Abstract

The characterization of the aggregation kinetics of protein amyloids and the structural properties of the ensuing aggregates are vital in the study of the pathogenesis of many neurodegenerative diseases and the discovery of therapeutic targets. In this article, we show that the fluorescence lifetime of synthetic dyes covalently attached to amyloid proteins informs on the structural properties of amyloid clusters formed both in vitro and in cells. We demonstrate that the mechanism behind such a “lifetime sensor” of protein aggregation is based on fluorescence self-quenching and that it offers a good dynamic range to report on various stages of aggregation without significantly perturbing the process under investigation. We show that the sensor informs on the structural density of amyloid clusters in a high-throughput and quantitative manner and in these aspects the sensor outperforms super-resolution imaging techniques. We demonstrate the power and speed of the method, offering capabilities, for example, in therapeutic screenings that monitor biological self-assembly. We investigate the mechanism and advantages of the lifetime sensor in studies of the K18 protein fragment of the Alzheimer’s disease related protein tau and its amyloid aggregates formed in vitro. Finally, we demonstrate the sensor in the study of aggregates of polyglutamine protein, a model used in studies related to Huntington’s disease, by performing correlative fluorescence lifetime imaging microscopy and structured-illumination microscopy experiments in cells.

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Research works printed but not linked: 43

  1. Sipe, 2000, J. Struct. Biol., 130, 88, 10.1006/jsbi.2000.4221 · DOI
  2. Bates, 2003, Lancet, 361, 1642, 10.1016/S0140-6736(03)13304-1 · DOI
  3. Aguzzi, 2010, Nat. Rev. Drug Discovery, 9, 237, 10.1038/nrd3050 · DOI
  4. Stefani, 2003, J. Mol. Med., 81, 678, 10.1007/s00109-003-0464-5 · DOI
  5. Bacskai, 2003, J. Biomed. Opt., 8, 368, 10.1117/1.1584442 · DOI
  6. Kollmer, 2016, Proc. Natl. Acad. Sci. U. S. A., 113, 5604, 10.1073/pnas.1523496113 · DOI
  7. Lu, 2015, Biotechnol. Bioeng., 112, 1883, 10.1002/bit.25606 · DOI
  8. Lu, 2015, J. Biol. Chem., 290, 27986, 10.1074/jbc.M115.676437 · DOI
  9. Guo, 2006, Biomacromolecules, 7, 1630, 10.1021/bm0600724 · DOI
  10. Stine, 1996, J. Protein Chem., 15, 193, 10.1007/BF01887400 · DOI
  11. Roberti, 2007, Nat. Methods, 4, 345, 10.1038/nmeth1026 · DOI
  12. Chan, 2013, Analyst, 138, 2156, 10.1039/c3an36798c · DOI
  13. Pinotsi, 2016, J. Am. Chem. Soc., 138, 3046, 10.1021/jacs.5b11012 · DOI
  14. Ries, 2013, ACS Chem. Neurosci., 4, 1057, 10.1021/cn400091m · DOI
  15. Esbjörner, 2014, Chem. Biol., 21, 732, 10.1016/j.chembiol.2014.03.014 · DOI
  16. Kaminski Schierle, 2011, J. Am. Chem. Soc., 133, 12902, 10.1021/ja201651w · DOI
  17. Pinotsi, 2014, Nano Lett., 14, 339, 10.1021/nl4041093 · DOI
  18. Laine, 2016, Methods Appl. Fluoresc., 4, 022004, 10.1088/2050-6120/4/2/022004 · DOI
  19. Kaminski, 2016, Neurophotonics, 3, 041807, 10.1117/1.NPh.3.4.041807 · DOI
  20. Quinn, 2014, Mol. BioSyst., 10, 34, 10.1039/C3MB70272C · DOI
  21. McGinty, 2011, Biomed. Opt. Express, 2, 1340, 10.1364/BOE.2.001340 · DOI
  22. Lakowicz, 2013, Principles of fluorescence spectroscopy
  23. Shammas, 2015, Nat. Commun., 6, 7025, 10.1038/ncomms8025 · DOI
  24. Ströhl, 2016, Optica, 3, 667, 10.1364/OPTICA.3.000667 · DOI
  25. Gustafsson, 2000, J. Microsc., 198, 82, 10.1046/j.1365-2818.2000.00710.x · DOI · Paper page
  26. Young, 2016, J. Visualized Exp., 111, e53988, 10.3791/53988 · DOI
  27. Gustafsson, 2008, Biophys. J., 94, 4957, 10.1529/biophysj.107.120345 · DOI
  28. Wicker, 2013, Opt. Express, 21, 24692, 10.1364/OE.21.024692 · DOI
  29. Shaw, 2015, Methods, 88, 11, 10.1016/j.ymeth.2015.03.020 · DOI
  30. Amaro, 2014, Appl. Phys. Lett., 104, 063704, 10.1063/1.4865197 · DOI
  31. Kaminski Schierle, 2011, ChemPhysChem, 12, 673, 10.1002/cphc.201000996 · DOI
  32. Frank, 2007, J. Microsc., 227, 203, 10.1111/j.1365-2818.2007.01803.x · DOI
  33. Warren, 2013, PLoS One, 8, e70687, 10.1371/journal.pone.0070687 · DOI
  34. Chen, 2015, Biophys. J., 108, 999, 10.1016/j.bpj.2015.01.012 · DOI
  35. Digman, 2008, Biophys. J., 94, L14, 10.1529/biophysj.107.120154 · DOI
  36. Redford, 2005, J. Fluoresc., 15, 805, 10.1007/s10895-005-2990-8 · DOI
  37. Clayton, 2004, J. Microsc., 213, 1, 10.1111/j.1365-2818.2004.01265.x · DOI
  38. Von Smoluchowski, 1917, Zeitschrift für physikalische Chemie, 92, 129
  39. Rice, 1985, Diffusion-limited reactions
  40. Dorsaz, 2010, Phys. Rev. Lett., 105, 120601, 10.1103/PhysRevLett.105.120601 · DOI
  41. Dean, 2014, Nat. Chem. Biol., 10, 512, 10.1038/nchembio.1556 · DOI
  42. McKay, 2014, Chem. Biol., 21, 1075, 10.1016/j.chembiol.2014.09.002 · DOI
  43. de Chaumont, 2012, Nat. Methods, 9, 690, 10.1038/nmeth.2075 · DOI

Cited by

Metadata

Authors
Chen, W., Young, L. J., Lu, M., Zaccone, A., Ströhl, F., Yu, N., Kaminski Schierle, G. S., & Kaminski, C. F.
Venue
Nano Letters
Published
2016-11-30
Volume
17
Issue
1
Pages
143-149
ISSN
  • 1530-6984
  • 1530-6992
Cited by
85
References
5
Language
en
Funders
  • Wellcome Trust (NA)
  • Medical Research Council (NA)
  • Engineering and Physical Sciences Research Council (NA)
  • Biotechnology and Biological Sciences Research Council (NA)
  • Alzheimer’s Research UK (NA)
  • Cambridge Commonwealth, European and International Trust (NA)
  • China Scholarship Council (NA)

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