Trajectory data of antero- and retrograde movement of mitochondria in living zebrafish larvae

Mieskes, Frank; Wehnekamp, Fabian; Plucinska, Gabriela; Thong, Rachel; Misgeld, Thomas und Lamb, Don C. (2020): Trajectory data of antero- and retrograde movement of mitochondria in living zebrafish larvae. In: Data in Brief, Bd. 29, 105280

Abstract

Recently, a large number of single particle tracking (SPT) approaches have been developed. Generally, SPT techniques can be split into two groups: ex post facto approaches where trajectory extraction is carried out after data acquisition and feedback based approaches that perform particle tracking in real time [1]. One feedback approach is 3D Orbital Tracking, where the laser excitation beam is rotated in a circle about the object, generating a so called orbit [2,3]. By calculating the particle position from the detected intensity after every orbit in relation to its center, this method allows the microscope to follow a single object in real time. The high spatiotemporal resolution of this method and the potential to optically manipulate the followed object during the measurement promises to yield new deep insights into biological systems [4-7]. By upgrading this approach in a way that the specimen is recentered by a xy-stage on the center of the microscope, particle tracking with this long-range tracking feature is no longer limited to the covered field-of-view. This allows for the observation of mitochondrial trafficking in living zebrafish embryos over long distances. Here, we provide the raw data for antero- and retrograde movement of mitochondria labelled with photo-activatable green fluorescent protein (mitoPAGFP). It relates to the scientific article "Nanoresolution real-time 3D orbital tracking for studying mitochondrial trafficking in vertebrate axons in vivo" [8]. By applying a correlation analysis on the trajectories, it is possible to distinguish between active transport and pausing events with less biasing compared to the mean squared displacement approach. (C) 2020 The Authors. Published by Elsevier Inc.

• Dokumententyp: Zeitschriftenartikel
• Fakultät: Chemie und Pharmazie > Department Chemie ; Medizin > Munich Cluster for Systems Neurology (SyNergy)
• Fakultätsübergreifende Einrichtungen: Center for NanoScience (CENS)
• Themengebiete: 500 Naturwissenschaften und Mathematik > 540 Chemie ; 500 Naturwissenschaften und Mathematik > 500 Naturwissenschaften
• ISSN: 2352-3409
• Sprache: Englisch
• DFG: Gefördert durch die Deutsche Forschungsgemeinschaft (DFG) - 390857198