@article{BritzMarkertWitvlietetal.2021,
  author    = {Britz, Sebastian and Markert, Sebastian Matthias and Witvliet, Daniel and Steyer, Anna Maria and Tr{\"o}ger, Sarah and Mulcahy, Ben and Kollmannsberger, Philip and Schwab, Yannick and Zhen, Mei and Stigloher, Christian},
  title     = {Structural Analysis of the Caenorhabditis elegans Dauer Larval Anterior Sensilla by Focused Ion Beam-Scanning Electron Microscopy},
  series = {Frontiers in Neuroanatomy},
  volume    = {15},
  journal   = {Frontiers in Neuroanatomy},
  issn      = {1662-5129},
  doi       = {10.3389/fnana.2021.732520},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-249622},
  year      = {2021},
  abstract  = {At the end of the first larval stage, the nematode Caenorhabditis elegans developing in harsh environmental conditions is able to choose an alternative developmental path called the dauer diapause. Dauer larvae exhibit different physiology and behaviors from non-dauer larvae. Using focused ion beam-scanning electron microscopy (FIB-SEM), we volumetrically reconstructed the anterior sensory apparatus of C. elegans dauer larvae with unprecedented precision. We provide a detailed description of some neurons, focusing on structural details that were unknown or unresolved by previously published studies. They include the following: (1) dauer-specific branches of the IL2 sensory neurons project into the periphery of anterior sensilla and motor or putative sensory neurons at the sub-lateral cords; (2) ciliated endings of URX sensory neurons are supported by both ILso and AMso socket cells near the amphid openings; (3) variability in amphid sensory dendrites among dauers; and (4) somatic RIP interneurons maintain their projection into the pharyngeal nervous system. Our results support the notion that dauer larvae structurally expand their sensory system to facilitate searching for more favorable environments.},
  language  = {en}
}
@article{KaltdorfTheissMarkertetal.2018,
  author    = {Kaltdorf, Kristin Verena and Theiss, Maria and Markert, Sebastian Matthias and Zhen, Mei and Dandekar, Thomas and Stigloher, Christian and Kollmannsberger, Philipp},
  title     = {Automated classification of synaptic vesicles in electron tomograms of C. elegans using machine learning},
  series = {PLoS ONE},
  volume    = {13},
  journal   = {PLoS ONE},
  number    = {10},
  doi       = {10.1371/journal.pone.0205348},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-176831},
  pages     = {e0205348},
  year      = {2018},
  abstract  = {Synaptic vesicles (SVs) are a key component of neuronal signaling and fulfil different roles depending on their composition. In electron micrograms of neurites, two types of vesicles can be distinguished by morphological criteria, the classical "clear core" vesicles (CCV) and the typically larger "dense core" vesicles (DCV), with differences in electron density due to their diverse cargos. Compared to CCVs, the precise function of DCVs is less defined. DCVs are known to store neuropeptides, which function as neuronal messengers and modulators [1]. In C. elegans, they play a role in locomotion, dauer formation, egg-laying, and mechano- and chemosensation [2]. Another type of DCVs, also referred to as granulated vesicles, are known to transport Bassoon, Piccolo and further constituents of the presynaptic density in the center of the active zone (AZ), and therefore are important for synaptogenesis [3]. To better understand the role of different types of SVs, we present here a new automated approach to classify vesicles. We combine machine learning with an extension of our previously developed vesicle segmentation workflow, the ImageJ macro 3D ART VeSElecT. With that we reliably distinguish CCVs and DCVs in electron tomograms of C. elegans NMJs using image-based features. Analysis of the underlying ground truth data shows an increased fraction of DCVs as well as a higher mean distance between DCVs and AZs in dauer larvae compared to young adult hermaphrodites. Our machine learning based tools are adaptable and can be applied to study properties of different synaptic vesicle pools in electron tomograms of diverse model organisms.},
  language  = {en}
}