Fully automated head-twitch detection system for the study of 5-HT2A receptor pharmacology in vivo

Autor: Mario de la Fuente Revenga, Hiba Z. Vohra, Javier González-Maeso, Jong M. Shin, Matthew B. Schneck, Justin L. Poklis, Kelsey S. Hideshima
Rok vydání: 2019
Předmět:
Zdroj: Scientific Reports, Vol 9, Iss 1, Pp 1-14 (2019)
ISSN: 2045-2322
DOI: 10.1038/s41598-019-49913-4
Popis: Head-twitch behavior (HTR) is the behavioral signature of psychedelic drugs upon stimulation of the serotonin 5-HT2A receptor (5-HT2AR) in rodents. Following the previous report of a semi-automated detection of HTR based on the dynamics of mouse’s head movement, here we present a system for the identification of individual HTR events in a fully automated fashion. The validity of this fully automated HTR detection system was tested with the psychedelic drug DOI in 5-HT2AR-KO mice, and via evaluation of potential sources of false-positive and false-negative HTR events. The increased throughput in data processing achieved via automation afforded the possibility of conducting otherwise time consuming HTR time-course studies. To further assess the versatility of our system, we also explored the pharmacological interactions between 5-HT2AR and the metabotropic glutamate receptor 2 (mGluR2). Our data demonstrate the potentiation effect of the mGluR2/3 antagonist LY341495 on DOI-induced HTR, as well as the HTR-blocking effect of the mGluR2/3 agonist and antipsychotic drug in development LY404039. This fully automated system can contribute to speed up our understanding of 5-HT2AR’s pharmacology and its characteristic behavioral outputs in rodents.
Databáze: OpenAIRE