Identification of SSRI-evoked antidepressant sensory signals by decoding vagus nerve activity Journal Articles uri icon

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  • AbstractThe vagus nerve relays mood-altering signals originating in the gut lumen to the brain. In mice, an intact vagus is required to mediate the behavioural effects of both intraluminally applied selective serotonin reuptake inhibitors and a strain of Lactobacillus with antidepressant-like activity. Similarly, the prodepressant effect of lipopolysaccharide is vagus nerve dependent. Single vagal fibres are broadly tuned to respond by excitation to both anti- and prodepressant agents, but it remains unclear how neural responses encode behaviour-specific information. Here we demonstrate using ex vivo experiments that for single vagal fibres within the mesenteric neurovascular bundle supplying the mouse small intestine, a unique neural firing pattern code is common to both chemical and bacterial vagus-dependent antidepressant luminal stimuli. This code is qualitatively and statistically discernible from that evoked by lipopolysaccharide, a non-vagus-dependent antidepressant or control non-antidepressant Lactobacillus strain and are not affected by sex status. We found that all vagus dependent antidepressants evoked a decrease in mean spike interval, increase in spike burst duration, decrease in gap duration between bursts and increase in intra-burst spike intervals. Our results offer a novel neuronal electrical perspective as one explanation for mechanisms of action of gut-derived vagal dependent antidepressants. We expect that our ex vivo individual vagal fibre recording model will improve the design and operation of new, extant electroceutical vagal stimulation devices currently used to treat major depression. Furthermore, use of this vagal antidepressant code should provide a valuable screening tool for novel potential oral antidepressant candidates in preclinical animal models.


  • West, Christine L
  • McVey Neufeld, Karen-Anne
  • Mao, Yu-Kang
  • Stanisz, Andrew M
  • Forsythe, Paul
  • Bienenstock, John
  • Barbut, Denise
  • Zasloff, Michael
  • Kunze, Wolfgang

publication date

  • October 26, 2021