@article{JanschZieglerForeroetal.2021,
  author    = {Jansch, Charline and Ziegler, Georg C. and Forero, Andrea and Gredy, Sina and W{\"a}ldchen, Sina and Vitale, Maria Rosaria and Svirin, Evgeniy and Z{\"o}ller, Johanna E. M. and Waider, Jonas and G{\"u}nther, Katharina and Edenhofer, Frank and Sauer, Markus and Wischmeyer, Erhard and Lesch, Klaus-Peter},
  title     = {Serotonin-specific neurons differentiated from human iPSCs form distinct subtypes with synaptic protein assembly},
  series = {Journal of Neural Transmission},
  volume    = {128},
  journal   = {Journal of Neural Transmission},
  number    = {2},
  issn      = {1435-1463},
  doi       = {10.1007/s00702-021-02303-5},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-268519},
  pages     = {225-241},
  year      = {2021},
  abstract  = {Human induced pluripotent stem cells (hiPSCs) have revolutionized the generation of experimental disease models, but the development of protocols for the differentiation of functionally active neuronal subtypes with defined specification is still in its infancy. While dysfunction of the brain serotonin (5-HT) system has been implicated in the etiology of various neuropsychiatric disorders, investigation of functional human 5-HT specific neurons in vitro has been restricted by technical limitations. We describe an efficient generation of functionally active neurons from hiPSCs displaying 5-HT specification by modification of a previously reported protocol. Furthermore, 5-HT specific neurons were characterized using high-end fluorescence imaging including super-resolution microscopy in combination with electrophysiological techniques. Differentiated hiPSCs synthesize 5-HT, express specific markers, such as tryptophan hydroxylase 2 and 5-HT transporter, and exhibit an electrophysiological signature characteristic of serotonergic neurons, with spontaneous rhythmic activities, broad action potentials and large afterhyperpolarization potentials. 5-HT specific neurons form synapses reflected by the expression of pre- and postsynaptic proteins, such as Bassoon and Homer. The distribution pattern of Bassoon, a marker of the active zone along the soma and extensions of neurons, indicates functionality via volume transmission. Among the high percentage of 5-HT specific neurons (~ 42\%), a subpopulation of CDH13 + cells presumably designates dorsal raphe neurons. hiPSC-derived 5-HT specific neuronal cell cultures reflect the heterogeneous nature of dorsal and median raphe nuclei and may facilitate examining the association of serotonergic neuron subpopulations with neuropsychiatric disorders.},
  language  = {en}
}
@article{HepbasliGredyUllrichetal.2021,
  author    = {Hepbasli, Denis and Gredy, Sina and Ullrich, Melanie and Reigl, Amelie and Abeßer, Marco and Raabe, Thomas and Schuh, Kai},
  title     = {Genotype- and Age-Dependent Differences in Ultrasound Vocalizations of SPRED2 Mutant Mice Revealed by Machine Deep Learning},
  series = {Brain Sciences},
  volume    = {11},
  journal   = {Brain Sciences},
  number    = {10},
  issn      = {2076-3425},
  doi       = {10.3390/brainsci11101365},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-248525},
  year      = {2021},
  abstract  = {Vocalization is an important part of social communication, not only for humans but also for mice. Here, we show in a mouse model that functional deficiency of Sprouty-related EVH1 domain-containing 2 (SPRED2), a protein ubiquitously expressed in the brain, causes differences in social ultrasound vocalizations (USVs), using an uncomplicated and reliable experimental setting of a short meeting of two individuals. SPRED2 mutant mice show an OCD-like behaviour, accompanied by an increased release of stress hormones from the hypothalamic-pituitary-adrenal axis, both factors probably influencing USV usage. To determine genotype-related differences in USV usage, we analyzed call rate, subtype profile, and acoustic parameters (i.e., duration, bandwidth, and mean peak frequency) in young and old SPRED2-KO mice. We recorded USVs of interacting male and female mice, and analyzed the calls with the deep-learning DeepSqueak software, which was trained to recognize and categorize the emitted USVs. Our findings provide the first classification of SPRED2-KO vs. wild-type mouse USVs using neural networks and reveal significant differences in their development and use of calls. Our results show, first, that simple experimental settings in combination with deep learning are successful at identifying genotype-dependent USV usage and, second, that SPRED2 deficiency negatively affects the vocalization usage and social communication of mice.},
  language  = {en}
}