@phdthesis{Kropf2018,
  author    = {Kropf, Jan},
  title     = {The Dual Olfactory Pathway in the Honeybee Brain: Sensory Supply and Electrophysiological Properties},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-108369},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2018},
  abstract  = {The olfactory sense is of utmost importance for honeybees, Apis mellifera. Honeybees use olfaction for communication within the hive, for the identification of nest mates and non-nest mates, the localization of food sources, and in case of drones (males), for the detection of the queen and mating. Honeybees, therefore, can serve as excellent model systems for an integrative analysis of an elaborated olfactory system. To efficiently filter odorants out of the air with their antennae, honeybees possess a multitude of sensilla that contain the olfactory sensory neurons (OSN). Three types of olfactory sensilla are known from honeybee worker antennae: Sensilla trichoidea, Sensilla basiconica and Sensilla placodea. In the sensilla, odorant receptors that are located in the dendritic arborizations of the OSNs transduce the odorant information into electrical information. Approximately 60.000 OSN axons project in two parallel bundles along the antenna into the brain. Before they enter the primary olfactory brain center, the antennal lobe (AL), they diverge into four distinct tracts (T1-T4). OSNs relay onto ~3.000-4.000 local interneurons (LN) and ~900 projection neurons (PN), the output neurons of the AL. The axons of the OSNs together with neurites from LNs and PNs form spheroidal neuropil units, the so-called glomeruli. OSN axons from the four AL input tracts (T1-T4) project into four glomerular clusters. LNs interconnect the AL glomeruli, whereas PNs relay the information to the next brain centers, the mushroom body (MB) - associated with sensory integration, learning and memory - and the lateral horn (LH). In honeybees, PNs project to the MBs and the LH via two separate tracts, the medial and the lateral antennal-lobe tract (m/lALT) which run in parallel in opposing directions. The mALT runs first to the MB and then to the LH, the lALT runs first to the LH and then to the MB. This dual olfactory pathway represents a feature unique to Hymenoptera. Interestingly, both tracts were shown to process information about similar sets of odorants by extracting different features. Individual mALT PNs are more odor specific than lALT PNs. On the other hand, lALT PNs have higher spontaneous and higher odor response action potential (AP) frequencies than mALT PNs. In the MBs, PNs form synapses with ~184.000 Kenyon cells (KC), which are the MB intrinsic neurons. KCs, in contrast to PNs, show almost no spontaneous activity and employ a spatially and temporally sparse code for odor coding. In manuscript I of my thesis, I investigated whether the differences in specificity of odor responses between m- and lALT are due to differences in the synaptic input. Therefore, I investigated the axonal projection patterns of OSNs housed in S. basiconica in honeybee workers and compared them with S. trichoidea and S. placodea using selective anterograde labeling with fluorescent tracers and confocal- microscopy analyses of axonal projections in AL glomeruli. Axons of S. basiconica-associated OSNs preferentially projected into the T3 input-tract cluster in the AL, whereas the two other types of sensilla did not show a preference for a specific glomerular cluster. T3- associated glomeruli had previously been shown to be innervated by mALT PNs. Interestingly, S. basiconica as well as a number of T3 glomeruli lack in drones. Therefore I set out to determine whether this was associated with the reduction of glomeruli innervated by mALT PNs. Retrograde tracing of mALT PNs in drones and counting of innervated glomeruli showed that the number of mALT-associated glomeruli was strongly reduced in drones compared to workers. The preferential projections of S. basiconica-associated OSNs into T3 glomeruli in female workers together with the reduction of mALT-associated glomeruli in drones support the presence of a female-specific olfactory subsystem that is partly innervated by OSNs from S. basiconica and is associated with mALT projection neurons. As mALT PNs were shown to be more odor specific, I suppose that already the OSNs in this subsystem are more odor specific than lALT associated OSNs. I conclude that this female-specific subsystem allows the worker honeybees to respond adequately to the enormous variety of odorants they experience during their lifetime. In manuscript II, I investigated the ion channel composition of mALT and lALT PNs and KCs in situ. This approach represents the first study dealing with the honeybee PN and KC ion channel composition under standard conditions in an intact brain preparation. With these recordings I set out to investigate the potential impact of intrinsic neuronal properties on the differences between m- and lALT PNs and on the sparse odor coding properties of KCs. In PNs, I identified a set of Na+ currents and diverse K+ currents depending on voltage and Na+ or Ca2+ that support relatively high spontaneous and odor response AP frequencies. This set of currents did not significantly differ between mALT and lALT PNs, but targets for potential modulation of currents leading to differences in AP frequencies were found between both types of PNs. In contrast to PNs, KCs have very prominent K+ currents, which are likely to contribute to the sparse response fashion observed in KCs. Furthermore, Ca2+ dependent K+ currents were found, which may be of importance for coincidence detection, learning and memory formation. Finally, I conclude that the differences in odor specificity between m- and lALT PNs are due to their synaptic input from different sets of OSNs and potential processing by LNs. The differences in spontaneous activity between the two tracts may be caused by different neuronal modulation or, in addition, also by interaction with LNs. The temporally sparse representation of odors in KCs is very likely based on the intrinsic KC properties, whereas general excitability and spatial sparseness are likely to be regulated through GABAergic feedback neurons.},
  subject      = {Voltage-Clamp-Methode},
  language  = {en}
}
@phdthesis{Saumweber2011,
  author    = {Saumweber, Timo},
  title     = {Mechanism of Learning and Plasticity in Larval Drosophila},
  url       = {http://nbn-resolving.de/urn:nbn:de:bvb:20-opus-66354},
  school      = {Universit{\"a}t W{\"u}rzburg},
  year      = {2011},
  abstract  = {According to a changing environment it is crucial for animals to make experience and learn about it. Sensing, integrating and learning to associate different kinds of modalities enables animals to expect future events and to adjust behavior in the way, expected as the most profitable. Complex processes as memory formation and storage make it necessary to investigate learning and memory on different levels. In this context Drosophila melanogaster represents a powerful model organism. As the adult brain of the fly is still quite complex, I chose the third instar larva as model - the more simple the system, the easier to isolate single, fundamental principles of learning. In this thesis I addressed several kinds of questions on different mechanism of olfactory associative and synaptic plasiticity in Drosophila larvae. I focused on short-term memory throughout my thesis. First, investigating larval learning on behavioral level, I developed a one-odor paradigm for olfactory associative conditioning. This enables to estimate the learnability of single odors, reduces the complexity of the task and simplify analyses of "learning mutants". It further allows to balance learnability of odors for generalization-type experiments to describe the olfactory "coding space". Furthermore I could show that innate attractiveness and learnability can be dissociated and found finally that paired presentation of a given odor with reward increase performance, whereas unpaired presentations of these two stimuli decrease performance, indicating that larva are able to learn about the presence as well as about the absence of a reward. Second, on behavioral level, together with Thomas Niewalda and colleagues we focussed on salt processing in the context of choice, feeding and learning. Salt is required in several physiological processes, but can neither be synthesized nor stored. Various salt concentrations shift the valence from attraction to repulsion in reflexive behaviour. Interestingly, the reinforcing effect of salt in learning is shifted by more than one order of magnitude toward higher concentrations. Thus, the input pathways for gustatory behavior appear to be more sensitive than the ones supporting gustatory reinforcement, which is may be due to the dissociation of the reflexive and the reinforcing signalling pathways of salt. Third, in cooperation with Michael Schleyer we performed a series of behavioral gustatory, olfactory preference tests and larval learning experiments. Based on the available neuroanatomical and behavioral data we propose a model regarding chemosensory processing, odor-tastant memory trace formation and the 'decision' like process. It incorporates putative sites of interaction between olfactory and gustatory pathways during the establishment as well as behavioral expression of odor-tastant memory. We claim that innate olfactory behavior is responsive in nature and suggest that associative conditioned behavior is not a simple substitution like process, but driven more likely by the expectation of its outcome. Fourth, together with Birgit Michels and colleagues we investigated the cellular site and molecular mode of Synapsin, an evolutionarily conserved, presynaptic vesicular phosphoprotein and its action in larval learning. We confirmed a previously described learning impairment upon loss of Synapsin. We localized this Synapsin dependent memory trace in the mushroom bodies, a third-order "cortical" brain region, and could further show on molecular level, that Synapsin is as a downstream element of the AC-cAMP-PKA signalling cascade. This study provides a comprehensive chain of explanation from the molecular level to an associative behavioral change. Fifth, in the main part of my thesis I focused on molecular level on another synaptic protein, the Synapse associated protein of 47kDa (Sap47) and its role in larval behavior. As a member of a phylogenetically conserved gene family of hitherto unknown function. It is localized throughout the whole neuropil of larval brains and associated with presynaptic vesicles. Upon loss of Sap47 larvae exhibit normal sensory detection of the to-be-associated stimuli as well as normal motor performance and basic synaptic transmission. Interestingly, short-term plasticity is distorted and odorant-tastant associative learning ability is reduced. This defect in associative function could be rescued by restoring Sap47 expression. Therefore, this report is the first to suggest a function for Sap47 and specifically argues that Sap47 is required for synaptic as well as for behavioral plasticity in Drosophila larva. This prompts the question whether its homologs are required for synaptic and behavioral plasticity also in other species. Further in the last part of my thesis I contributed to the study of Ayse Yarali. Her central topic was the role of the White protein in punishment and relief learning in adult flies. Whereas stimuli that precede shock during training are subsequently avoided as predictors for punishment, stimuli that follow shock during training are later on approached, as they predict relief. Concerning the loss of White we report that pain-relief learning as well as punishment learning is changed. My contribution was a comparison between wild type and the white1118 mutant larvae in odor-reward learning. It turned out that a loss of White has no effect on larval odorant-tastant learning. This study, regarding painrelief learning provides the very first hints concerning the genetic determinants of this form of learning.},
  subject      = {Taufliege},
  language  = {en}
}