Parallel multimodal circuits control an innate foraging behavior

Abstract

SUMMARYForaging strategies that enable animals to locate food efficiently are composed of highly conserved behavioral states with characteristic features. Here, we identify parallel multimodal circuit modules that control an innate foraging state --local search behavior --after food removal in the nematode Caenorhabditis elegans. Two parallel groups of chemosensory and mechanosensory glutamatergic neurons that detect food-related cues trigger local search by inhibiting separate integrating neurons through a metabotropic glutamate receptor, MGL-1. The chemosensory and mechanosensory modules are separate and redundant, as glutamate release from either can drive the full behavior. Spontaneous activity in the chemosensory module encodes information about the time since the last food encounter and correlates with the foraging behavior. In addition, the ability of the sensory modules to control local search is gated by the internal nutritional state of the animal. This multimodal circuit configuration provides robust control of an innate adaptive behavior.

Feeding state functionally reconfigures a sensory circuit to drive thermosensory behavioral plasticity

“…If AWC-mediated glutamatergic transmission inhibits temperature responses in AIA in starved animals, we would predict that blocking glutamatergic signaling from AWC would also be sufficient to restore negative thermotaxis upon starvation. Indeed, we found that knocking out the glutamate transporter eat-4 cell-specifically in AWC ( López-Cruz et al, 2019 ) resulted in robust negative thermotaxis behavior by starved animals ( Figure 3I ). These experiments suggest that upon prolonged starvation, increased AWC temperature responses inhibit AIA via glutamatergic signaling to disrupt negative thermotaxis via warming-uncorrelated regulation of reversals and turns.…”

“…Similar HisCl1-mediated silencing of the ASI bacteria-sensing neurons ( Gallagher et al, 2013 ) had no effect on the expected negative thermotaxis behaviors ( Figure 2—figure supplement 1C ). As an independent verification, we silenced AWC via cell-specific expression of the light-gated anion channelrhodopsin GtACR2 ( Govorunova et al, 2015 ; López-Cruz et al, 2019 ). Optogenetic silencing of AWC during the assay was again sufficient to restore negative thermotaxis bias in starved animals ( Figure 2B ).…”

“…Increasing AWC activity either via genetic or optogenetic means has previously been shown to promote reversals and turns via inhibition and activation of the postsynaptic primary layer interneurons AIY and AIA, and AIB, respectively ( Figure 3A ; Albrecht and Bargmann, 2011 ; Chalasani et al, 2007 ; Chalasani et al, 2010 ; Gordus et al, 2015 ; Gray et al, 2005 ; White et al, 1986 ). Consequently, AIY and AIA inhibit, and AIB promotes, reversals and/or turns ( Figure 3A ; Chalasani et al, 2007 ; Gordus et al, 2015 ; Gray et al, 2005 ; Kocabas et al, 2012 ; Li et al, 2014 ; López-Cruz et al, 2019 ; Tsalik and Hobert, 2003 ; Wakabayashi et al, 2004 ). Enhanced AWC activity in starved animals is consistent with our observation that animals exhibit increased reversals and turns at the starting temperature upon food deprivation ( Figure 1B ), thereby failing to correctly navigate the spatial thermal gradient.…”

“…( I ) Mean thermotaxis bias of animals of the indicated genotypes. eat-4 was knocked out in AWC via FLP-FRT-mediated recombination ( López-Cruz et al, 2019 ). Each dot represents the thermotaxis bias of a biologically independent assay comprised of 15 animals.…”

“…We suggest that incorporating distinct modulatory pathways as a function of different experiences and conditions allows for a greater degree of behavioral flexibility and more efficient behavioral reprioritization, as compared to direct modulation of the core circuit itself, particularly in small circuits. Food deprivation for different periods of time has been shown to result in distinct behavioral changes that may be physiologically relevant in terms of driving specific food-seeking behaviors ( Churgin et al, 2017 ; Farhadian et al, 2012 ; Ghosh et al, 2016 ; Gray et al, 2005 ; Inagaki et al, 2014 ; Lee and Park, 2004 ; López-Cruz et al, 2019 ; Neal et al, 2015 ; Root et al, 2011 ; Tsalik and Hobert, 2003 ). These changes may be driven via temporally regulated recruitment of different neuronal pathways to functionally reconfigure the core sensorimotor circuit and reprioritize behaviors ( Churgin et al, 2017 ; Ghosh et al, 2016 ; Gray et al, 2005 ; Inagaki et al, 2012 ; Saeki et al, 2001 ).…”