Toponome
editThe toponome is the spatial network code of proteins and other biomolecules in morphologically intact cells and tissues.[1] It is mapped and decoded by imaging cycler microscopy (ICM) in situ able to co-map many thousand supermolecules in one sample (tissue section or cell sample at high subcellular resolution). The term “toponome” is derived from the ancient Greek nouns “topos” (τόπος; place, position) and “nomos” (νόμος; law). It was introduced by Walter Schubert in 2003 [2]. It addresses the fact that the network of biomolecules in cells and tissues follows topological rules enabling coordinated actions. For example, the cell surface toponome provides the spatial protein interaction code for the execution of a cell movement, a „code of conduct“ [2][3][4]. This is intrinsically dependent on the specific spatial arrangement of similar and dissimilar compositions of supermolecules (compositional periodicity) with a specific spatial order along a cell surface membrane. This spatial order is periodically repeated when the cell tries to enter the exploratory state from the spherical state (spatial periodicity).[5] This spatial toponome code is hierarchically organized with lead biomolecule(s), anti-colocated (absent) biomolecule(s)[2][3] and wildcard molecules which are variably associated with the lead biomolecule(s). It has been shown that inhibition of lead molecule(s) in a surface membrane leads to disassembly of the corresponding biomolecular network and loss of function [3][4].
Citations
edit- ^ Schubert, W (2013). "Toponomics" in Dubitzky, Wolkenhauer, Cho, Yokota. Encyclopedia of Systems Biology. Springer New York. pp. 2191–2212. ISBN 978-1-4419-9862-0.
- ^ a b c Schubert, W (2003). "Topological Proteomics, Toponomics, MELK-Technology". Advances in Biochemical Engineering/Biotechnology. 83: 189–209. doi:10.1007/3-540-36459-5_8.
- ^ a b c Schubert, Walter (1 October 2006). "Analyzing proteome topology and function by automated multidimensional fluorescence microscopy". Nature Biotechnology. 24 (10): 1270–1278. doi:10.1038/nbt1250.
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: Unknown parameter|coauthors=
ignored (|author=
suggested) (help) - ^ a b Schubert, Walter (15 September 2010). "On the origin of cell functions encoded in the toponome". Journal of Biotechnology. 149 (4): 252–259. doi:10.1016/j.jbiotec.2010.03.009.
- ^ Schubert, Walter (January 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.
Toponomics
editToponomics is a discipline in systems biology, molecular cell biology, and histology[1][2]. It concerns the study of the toponome of organisms. The toponome is the spatial network code of proteins and other biomolecules in morphologically intact cells and tissues [2][3]. The terms toponome and toponomics were introduced by Walter Schubert in 2003[1] based on observations with imaging cycler microscopes (ICM). The term “toponome” is derived from the ancient Greek nouns “topos” (τόπος; place, position) and “nomos” (νόμος; law). Hence the term toponomics is descriptive term addressing the fact that the spatial network of biomolecules in cells follows topological rules enabling coordinated actions [1]. This spatial organization is directly revealed by imaging cycler microscopy with parameter- and dimension-unlimited functional resolution. The resulting toponome structures are hierarchically organized and can be described by a three symbol code [1][3][4][5]. Toponomics is the field of study that has at its goal to decode the complete toponome in health and disease (The human toponome project[6]) - the next big challenge in human biotechnology after having decoded the human genome[6][7].
Citations
edit- ^ a b c d Schubert, W (2003). "Topological Proteomics, Toponomics, MELK-Technology". Advances in Biochemical Engineering/Biotechnology. 83: 189–209. doi:10.1007/3-540-36459-5_8.
- ^ a b Schubert, W (2013). "Toponomics" in Dubitzky, Wolkenhauer, Cho, Yokota. Encyclopedia of Systems Biology. Springer New York. pp. 2191–2212. ISBN 978-1-4419-9862-0.
- ^ a b Schubert, Walter (1 October 2006). "Analyzing proteome topology and function by automated multidimensional fluorescence microscopy". Nature Biotechnology. 24 (10): 1270–1278. doi:10.1038/nbt1250.
{{cite journal}}
: Unknown parameter|coauthors=
ignored (|author=
suggested) (help) - ^ 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.
- ^ 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.
- ^ a b 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.
- ^ Abott, A (12 October 2006). ""Mapping togetherness" (research highlight refering to Schubert et.al. 2006)". Nature. 443 (7112): 608–609. doi:10.1038/443608a.
Imaging Cycler Microscopy
editAn imaging cycler microscope (ICM) is a fully automated (epi)fluorescence microscope which overcomes the spectral resolution limit resulting in paramater- and dimension-unlimited florescence 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. Imacing Cycler Microscopy received the american ISAC best paper award in 2008 for the three symbol code of organized proteomes [11].
Citations
edit- ^ a b 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)].
- ^ a b 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.
- ^ a b Schubert, Walter (1 October 2006). "Analyzing proteome topology and function by automated multidimensional fluorescence microscopy". Nature Biotechnology. 24 (10): 1270–1278. doi:10.1038/nbt1250.
{{cite journal}}
: Unknown parameter|coauthors=
ignored (|author=
suggested) (help) - ^ Friedenberger, Manuela (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.
{{cite journal}}
: Unknown parameter|coauthors=
ignored (|author=
suggested) (help) - ^ a b 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.
- ^ 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.
- ^ Micheva, Kristina D. (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.
{{cite journal}}
: Unknown parameter|coauthors=
ignored (|author=
suggested) (help) - ^ Gerdes, M. J. (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 journal}}
: Unknown parameter|coauthors=
ignored (|author=
suggested) (help) - ^ Schubert, W. (7 January 2014). "Imaging cycler microscopy". Proceedings of the National Academy of Sciences. 111 (2): E215–E215. doi:10.1073/pnas.1319017111.
{{cite journal}}
: Unknown parameter|coauthors=
ignored (|author=
suggested) (help) - ^ 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.
- ^ 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.