Decoding the intensity of sensory input by two glutamate receptors in one C. elegans interneuron

Wenjuan Zou, Jiajun Fu, Haining Zhang, Kang Du, Wenming Huang, Junwei Yu, Shitian Li, Yuedan Fan, Howard A. Baylis, Shangbang Gao, Rui Xiao, Wei Ji (), Lijun Kang () and Tao Xu ()
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Wenjuan Zou: Chinese Academy of Sciences
Jiajun Fu: Chinese Academy of Sciences
Haining Zhang: Chinese Academy of Sciences
Kang Du: Huazhong University of Science and Technology
Wenming Huang: Huazhong University of Science and Technology
Junwei Yu: Chinese Academy of Sciences
Shitian Li: Zhejiang University School of Medicine
Yuedan Fan: Zhejiang University School of Medicine
Howard A. Baylis: University of Cambridge
Shangbang Gao: Huazhong University of Science and Technology
Rui Xiao: University of Florida
Wei Ji: University of Chinese Academy of Sciences
Lijun Kang: Zhejiang University School of Medicine
Tao Xu: Chinese Academy of Sciences

Nature Communications, 2018, vol. 9, issue 1, 1-12

Abstract: Abstract How neurons are capable of decoding stimulus intensity and translate this information into complex behavioral outputs is poorly defined. Here, we demonstrate that the C. elegans interneuron AIB regulates two types of behaviors: reversal initiation and feeding suppression in response to different concentrations of quinine. Low concentrations of quinine are decoded in AIB by a low-threshold, fast-inactivation glutamate receptor GLR-1 and translated into reversal initiation. In contrast, high concentrations of quinine are decoded by a high-threshold, slow-inactivation glutamate receptor GLR-5 in AIB. After activation, GLR-5 evokes sustained Ca2+ release from the inositol 1,4,5-trisphosphate (IP3)-sensitive Ca2+ stores and triggers neuropeptide secretion, which in turn activates the downstream neuron RIM and inhibits feeding. Our results reveal that distinct signal patterns in a single interneuron AIB can encode differential behavioral outputs depending on the stimulus intensity, thus highlighting the importance of functional mapping of information propagation at the single-neuron level during connectome construction.

Date: 2018
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DOI: 10.1038/s41467-018-06819-5

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