piwik-script

Zentrale Abteilung für Mikroskopie - Imaging Core Facility

Research: Synaptic architecture at the nano-scale

Neuronal synapses are highly efficient and complex cellular signaling machineries that achieve remarkable precision in signal transmission for a prolonged period of time, in some cases throughout the lifetime of an animal. The importance of synaptic efficiency is mirrored by many neural diseases but in particular by synaptopathies where synaptic organization and function is disrupted. In order to provide reliable signaling synaptic vesicles have to be retained close to the presynaptic active zone, the domain where vesicles are docked and fuse with the membrane after Ca influx in a nano-domain through voltage gated channels.
How are synaptic vesicles kept coherently close to the active zone to maintain efficient signaling? To shed light onto this question our team focuses on the cellular architecture using a combination of genetic tools and imaging techniques. In particular we apply electron tomography as ultra high 3D resolution method to dissect components and function of synaptic architecture. We use a synergistic combination of two highly tractable models where they are most appropriate: The C. elegans neuromuscular junctions for efficient candidate identification and manipulation and the neuromuscular junctions of the zebrafish larva as vertebrate model to test for evolutionary conservation of function.

2018

  • Beer, K.B., Rivas-Castillo, J., Kuhn, K., Fazeli, G., Karmann, B., Nance, J.F., Stigloher, C., Wehman, A.M. (2018) “Extracellular vesicle budding is inhibited by redundant regulators of TAT-5 flippase localization and phospholipid asymmetry”, Proceedings of the National Academy of Sciences, 115(6), E1127--E1136, available: https://www.pnas.org/content/115/6/E1127.
     
  • D'Alessandro, M., Richard, M., Stigloher, C., Vincent, G., Boulin, T., Richmond, J.E., Bessereau, J.-L. (2018) “CRELD1 is an evolutionarily-conserved maturational enhancer of ionotropic acetylcholine receptors”, eLife, 7(e39649), available: https://doi.org/10.7554/eLife.39649.
     
  • Böhm, J., Messerer, M., Müller, H.M., Scholz-Starke, J., Gradogna, A., Scherzer, S., Maierhofer, T., Bazihizina, N., Zhang, H., Stigloher, C., Ache, P., Al-Rasheid, K.A.S., Mayer, K.F.X., Shabala, S., Carpaneto, A., Haberer, G., Zhu, J.-K., Hedrich, R. (2018) “Understanding the Molecular Basis of Salt Sequestration in Epidermal Bladder Cells of Chenopodium quinoa, Current Biology, 28(19), 3075 - 3085.e7, available: http://www.sciencedirect.com/science/article/pii/S0960982218310492.
     
  • Spindler, M.-C., Helmprobst, F., Stigloher, C., Benavente, R. (2018) “EM Tomography of Meiotic LINC Complexes”, in Gundersen, G.G. and Worman, H.J., eds., The Linc Complex: Methods And Protocols, Springer New York: New York, NY, 3--15, available: https://doi.org/10.1007/978-1-4939-8691-0_1.
     
  • Kaltdorf, K.V., Theiss, M., Markert, S.M., Zhen, M., Dandekar, T., Stigloher, C., Kollmannsberger, P. (2018) “Automated classification of synaptic vesicles in electron tomograms of C. elegans using machine learning”, PLOS ONE, 13(10), 1-22, available: https://doi.org/10.1371/journal.pone.0205348.
     

2017

  • Schieber, N.L., Machado, P., Markert, S.M., Stigloher, C., Schwab, Y., Steyer, A.M. (2017) “Chapter 4 - Minimal resin embedding of multicellular specimens for targeted FIB-SEM imaging”, in Müller-Reichert, T. and Verkade, P., eds., Correlative Light And Electron Microscopy Iii, Methods In Cell Biology, Academic Press, 69 - 83, available: http://www.sciencedirect.com/science/article/pii/S0091679X17300493.
     
  • Markert, S.M., Bauer, V., Muenz, T.S., Jones, N.G., Helmprobst, F., Britz, S., Sauer, M., Rössler, W., Engstler, M., Stigloher, C. (2017) “Chapter 2 - 3D subcellular localization with superresolution array tomography on ultrathin sections of various species”, in Müller-Reichert, T. and Verkade, P., eds., Correlative Light And Electron Microscopy Iii, Methods In Cell Biology, Academic Press, 21 - 47, available: http://www.sciencedirect.com/science/article/pii/S0091679X17300481.
     
  • Kaltdorf, K.V., Schulze, K., Helmprobst, F., Kollmannsberger, P., Dandekar, T., Stigloher, C. (2017) “FIJI Macro 3D ART VeSElecT: 3D Automated Reconstruction Tool for Vesicle Structures of Electron Tomograms”, PLOS Computational Biology, 13(1), 1-21, available: https://doi.org/10.1371/journal.pcbi.1005317.
     
  • Helmprobst, F., Lillesaar, C., Stigloher, C. (2017) “Expression of sept3, sept5a and sept5b in the Developing and Adult Nervous System of the Zebrafish (Danio rerio)”, Frontiers in Neuroanatomy, 11, available: https://doi.org/10.3389%2Ffnana.2017.00006.
     

2016

  • Jahn, M.T., Markert, S.M., Ryu, T., Ravasi, T., Stigloher, C., Hentschel, U., Moitinho-Silva, L. (2016) “Shedding light on cell compartmentation in the candidate phylum Poribacteria by high resolution visualisation and transcriptional profiling”, Scientific Reports, 6, 35860--, available: https://doi.org/10.1038/srep35860.
     
  • Markert, S.M., Britz, S., Proppert, S., Lang, M., Witvliet, D., Mulcahy, B., Sauer, M., Zhen, M., Bessereau, J.-L., Stigloher, C. (2016) “Filling the gap: adding super-resolution to array tomography for correlated ultrastructural and molecular identification of electrical synapses at the C. elegans connectome”, Neurophotonics, 3(4), 041802, available: https://doi.org/10.1117%2F1.nph.3.4.041802.
     

2015

  • Helmprobst, F., Frank, M., Stigloher, C. (2015) “Presynaptic architecture of the larval zebrafish neuromuscular junction”, Journal of Comparative Neurology, 523(13), 1984-1997, available: https://onlinelibrary.wiley.com/doi/abs/10.1002/cne.23775.