Imaging cycler microscopy

An imaging cycler microscope (ICM) is a fully automated (epi)fluorescence microscope which overcomes the spectral resolution limit resulting in parameter- and dimension-unlimited fluorescence imaging. The principle and robotic device was described by Walter Schubert in 1997 [1] and eversince has been further developed with his co-workers within the human toponome project.[2][3][4][5] The ICM runs robotically controlled repetitive incubation-imaging-bleaching cycles with dye-conjugated probe libraries recognizing target structures in situ (biomolecules in fixed cells or tissue sections). This results in the transmission of a randomly large number of distinct biological informations by re-using the same fluorescence channel after bleaching for the transmission of another biological information using the same dye which is conjugated to another specific probe, a.s.o. Thereby noise-reduced quasi-multi channel fluorescence images with reproducible physical, geometrical, and biophyscial stabilities are generated. The resulting power of combinatorial molecular discrimination (PCMD) per data point is given by 65,536k, where 65,536 is the number of grey value levels (output of a 16-bit CCD camera) and k is the number of co-mapped biomolecules and/or subdomains per biomolecule(s). High PCMD has been shown for k = 100,[3][5] and in principle can be expanded for much higher numbers of k. In contrast to traditional multi-channel-few parameter fluorescence microscopy (Fig 1a) high PCMDs in an ICM lead to high functional and spatial resolution (Fig 1b). Systematic ICM analysis of biological systems reveals the supramolecular segregation law that describes the pinciple of order of large, hierarchically organized biomolecular networks in situ (toponome).[6] The ICM is the core technology for the systematic mapping of the complete protein network code in tissues (human toponome project).[2] The original ICM method [1] includes any modification of the bleaching step. Corresponding modifications have been reported for antibody retrieval [7] and chemical dye-quenching [8] debated recently.[9][10] The Toponome Imaging Systems (TIS) and Multi-Epitope-Ligand cartographs (MELC) represent different stages of the ICM technological development. Imaging Cycler Microscopy received the American ISAC best paper award in 2008 for the three symbol code of organized proteomes.[11]

Comparison of dimension-unlimited fluorescence imaging cycler microscopy (ICM) and standard three-parameter fluorescence microscopy.

Citations

  1. 1 2 Schubert W (1997) Automated device and method for measuring and identifying molecules or fragments thereof. European patent EP 0810428 B1 [see also Schubert W. US patent 6,150,173 (2000); Japanese patent 3739528 (1998)].
  2. 1 2 Cottingham, Katie (May 2008). "Human Toponome Project | Human Proteinpedia is open for (free) business". Journal of Proteome Research 7 (5): 1806–1806. doi:10.1021/pr083701k.
  3. 1 2 Schubert, Walter; Bonnekoh, Bernd; Pommer, Ansgar J; Philipsen, Lars; Böckelmann, Raik; Malykh, Yanina; Gollnick, Harald; Friedenberger, Manuela; Bode, Marcus; Dress, Andreas W M (1 October 2006). "Analyzing proteome topology and function by automated multidimensional fluorescence microscopy". Nature Biotechnology 24 (10): 1270–1278. doi:10.1038/nbt1250.
  4. Friedenberger, Manuela; Bode, Marcus; Krusche, Andreas; Schubert, Walter (September 2007). "Fluorescence detection of protein clusters in individual cells and tissue sections by using toponome imaging system: sample preparation and measuring procedures". Nature Protocols 2 (9): 2285–2294. doi:10.1038/nprot.2007.320.
  5. 1 2 Schubert, W. "Direct, spatial imaging of randomly large supermolecules by using parameter unlimited TIS imaging cycler microscopy." (PDF). International Microscopy Conference 2013. Retrieved 2013-09-23.
  6. Schubert, W (2014). "Systematic, spatial imaging of large multimolecular assemblies and the emerging principles of supramolecular order in biological systems.". Journal of Molecular Recognition 27 (1): 3–18. doi:10.1002/jmr.2326.
  7. Micheva, Kristina D.; Smith, Stephen J (July 2007). "Array Tomography: A New Tool for Imaging the Molecular Architecture and Ultrastructure of Neural Circuits". Neuron 55 (1): 25–36. doi:10.1016/j.neuron.2007.06.014.
  8. Gerdes, M. J.; Sevinsky, C. J.; Sood, A.; Adak, S.; Bello, M. O.; Bordwell, A.; Can, A.; Corwin, A.; Dinn, S.; Filkins, R. J.; Hollman, D.; Kamath, V.; Kaanumalle, S.; Kenny, K.; Larsen, M.; Lazare, M.; Li, Q.; Lowes, C.; McCulloch, C. C.; McDonough, E.; Montalto, M. C.; Pang, Z.; Rittscher, J.; Santamaria-Pang, A.; Sarachan, B. D.; Seel, M. L.; Seppo, A.; Shaikh, K.; Sui, Y.; Zhang, J.; Ginty, F. (1 July 2013). "Highly multiplexed single-cell analysis of formalin-fixed, paraffin-embedded cancer tissue". Proceedings of the National Academy of Sciences 110 (29): 11982–11987. doi:10.1073/pnas.1300136110. Cite uses deprecated parameter |coauthors= (help)
  9. Schubert, W.; Dress, A.; Ruonala, M.; Krusche, A.; Hillert, R.; Gieseler, A.; Walden, P. (7 January 2014). "Imaging cycler microscopy". Proceedings of the National Academy of Sciences 111 (2): E215–E215. doi:10.1073/pnas.1319017111.
  10. Gerdes, M. J. (7 January 2014). "Reply to Schubert et al.: Regarding critique of highly multiplexed technologies". Proceedings of the National Academy of Sciences 111 (2): E216–E216. doi:10.1073/pnas.1319622111.
  11. Schubert, Walter (June 2007). "A three-symbol code for organized proteomes based on cyclical imaging of protein locations". Cytometry Part A 71A (6): 352–360. doi:10.1002/cyto.a.20281.

References

Further reading

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