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Chemosensory Receptors in Berghia stephanieae: Bioinformatics and Localization

Chemosensation is achieved through the binding of chemical signals to chemoreceptor proteins embedded in the membranes of sensory neurons. The molecular identity of these receptors, as well as the downstream processing of chemosensory signals, has been well studied in arthropods and vertebrates. However, very little is known about molluscan chemosensation. The identity of chemoreceptor proteins in the nudibranch mollusc Berghia stephanieae are unknown. Data from other protostome and molluscan studies suggest Berghia may use ionotropic receptors for some forms of chemoreception. This study used a bioinformatics approach to identify potential chemosensory ionotropic receptors in the transcriptome of Berghia. A hidden Markov model program was used to generate molecular profiles of previously identified chemosensory receptors in other animals. A Berghia transcriptome was then searched for likely homologous sequences. Candidate sequences were investigated using protein prediction tools and molecular phylogenies. Fourteen ionotropic glutamate receptors (likely synaptic) and five divergent ionotropic receptors were identified. One of these divergent ionotropic receptor sequences, IR-D, may encode a chemosensory receptor and was therefore selected to determine its cellular expression in sensory and brain tissue using in situ hybridization chain reaction. Expression was seen in the rhinophores and oral tentacles of Berghia, as well as in the rhinophore ganglion, cerebral-pleural ganglion, and pedal ganglion. Similar expression patterns were obtained with tissue-specific transcriptomic data. This was the first study to investigate IR-D as a potential chemosensory receptor in molluscs, and thus has helped identify a new family of possible ionotropic chemoreceptor proteins in molluscs. These results have laid the groundwork for continued investigation of Berghia’s chemosensory system.

Identiferoai:union.ndltd.org:UMASS/oai:scholarworks.umass.edu:masters_theses_2-2309
Date28 October 2022
CreatorsWatkins, Kelsi L.
PublisherScholarWorks@UMass Amherst
Source SetsUniversity of Massachusetts, Amherst
Detected LanguageEnglish
Typetext
Formatapplication/pdf
SourceMasters Theses
Rightshttp://creativecommons.org/licenses/by-nc-nd/4.0/

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