Bao, Chenchang, Yang, Yanan, Zeng, Chaoshu, Huang, Huiyang, and Ye, Haihui (2018) Identifying neuropeptide GPCRs in the mud crab, Scylla paramamosain, by combinatorial bioinformatics analysis. General and Comparative Endocrinology, 269. pp. 122-130.

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Abstract

Neuropeptides, ubiquitous signaling molecules, commonly achieve their signaling function via interaction with cell membrane-spanning G-protein coupled receptors (GPCRs). In recent years, in the midst of the rapid development of next-generation sequencing technology, the amount of available information on encoded neuropeptides and their GPCRs sequences have increased dramatically. The repertoire of neuropeptides has been determined in many crustaceans, including the commercially important mud crab, Scylla paramamosain; however, determination of GPCRs is known to be more difficult and usually requires in vitro binding tests. In this study, we adopted a combinatorial bioinformatics analysis to identify S. paramamosain neuropeptide GPCRs. A total of 65 assembled GPCR sequences were collected from the transcriptome database. Subsequently these GPCRs were identified by comparison to known neuropeptide GPCRs based on the sequence-similarity-based clustering and phylogenetic analysis, which showed that many of them are closely related to insect GPCR families. Of these GPCRs, most of them were detected in various tissues of the mud crab and some of them showed differential expression by gender, suggesting they are involved in different physiological processes, such as sex differentiation. By employing ligand-receptor binding tests, we demonstrated that the predicted crustacean cardioactive peptide (CCAP) receptor was activated by CCAP peptide in a dose-dependent manner. This is the first CCAP receptor that has been functionally defined in crustaceans. In summary, the present study shortlists candidate neuropeptide GPCRs for ligand-receptor binding tests, and provides information for subsequent future research on the neuropeptide/GPCR signaling pathway in S. paramamosain.

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