Coordinated transcriptomics and peptidomics of central nervous system identify neuropeptides and their G protein-coupled receptors in the oriental fruit moth Grapholita molesta

Highlights

• The central nervous system transcriptome of G. molesta was successfully assembled.

• Total 57 neuropeptide precursor genes were identified.

• Total 28 peptides from 16 precursors were identified by peptidomic analysis.

• Total 41 G protein-coupled receptors for neuropeptides were identified.

• The expression profiles of 98 genes in different larval tissues were determined using qRT-PCR.

Abstract

The oriental fruit moth Grapholita molesta is a cosmopolitan pest of orchard, which causes serious economic losses to the fruit production. Neuropeptides and their specific receptors (primarily G protein-coupled receptors, GPCRs) regulate multiple biological functions in insects and represent promising next-generation pest management strategy. Here, we generated a transcriptome of the central nervous system (CNS) of G. molesta. Overall, 57 neuropeptide precursor genes were identified and 128 various mature peptides were predicted from these precursors. Using peptidomic analysis of CNS of G. molesta, we identified total of 28 mature peptides and precursor-related peptides from 16 precursors. A total of 41 neuropeptide GPCR genes belonging to three classes were also identified. These GPCRs and their probable ligands were predicted. Additionally, expression patterns of these 98 genes in various larval tissues were evaluated using quantitative real-time PCR. Taken together, these results will benefit further investigations to determine physiological functions and pharmacological characterization of neuropeptides and their GPCRs in G. molesta; and to develop specific neuropeptide-based agents for this tortricid fruit pest control.

Introduction

Physiological activities depend on many environmental (e.g., humidity, photoperiod) and intrinsic cues. Among the intrinsic cues, neuropeptides mainly produced from the central nervous system (CNS), are indispensable for regulating lots of neuro-endocrine activities (Menn and Borkovec, 1989; Nguyen et al., 2018). Neuropeptides represent the most diverse group of neural signaling molecules and play the critical role in the regulation of diverse basic activities, including feeding, excretion, behavior, growth, and reproduction (Ye et al., 2015; Ons, 2017). Neuropeptides are generated from single polypeptide precursors, which possess signal peptides and are cleaved and modified into bioactive mature peptides, then secreted into the extracellular parts (Hou et al., 2015). These bioactive mature peptides carry out their functions by binding to specific membrane receptors (mainly G protein-coupled receptors, GPCRs) (Xu et al., 2016). Seven α-helical transmembrane domains (TMDs) are characteristically a hallmark of neuropeptide GPCRs. Neuropeptide GPCRs can be divided into family A, family B, and leucine-rich repeat-containing GPCRs (LGRs) (Xu et al., 2019). Moreover, owing to the sequence-specificity of neuropeptides for the interaction with a unique receptor, neuropeptide mimetics would play a role in a species-specific way while leaving non target species unaffected (Ons, 2017). Therefore, insect neuropeptides and their GPCRs are attractive targets in developing next-generation pesticides (Iyison et al., 2021). Indeed, several insect analogues of neuropeptide have been shown to be insecticidal, such as capability-pyrokinin (CAPA-PK) (Gui et al., 2020), sulfakinin (SK) (Yu et al., 2013), and diapause hormone (DpH) (Zhang et al., 2011).

The oriental fruit moth, Grapholita molesta (Busck) (Lepidoptera: Tortricidae), is a major invasive pest on Rosaceae fruit trees worldwide (Yang et al., 2019). Management of G. molesta is challenging owing to its huge amounts of annual reproductive populations, generation overlap, host-transfer habit, small body size, and fruit-boring habit (Zhang et al., 2017; Zhang et al., 2019). Currently, main method to control G. molesta is to use conventional insecticides for eggs or neonate management (Wang et al., 2017). However, egg-stage monitoring is very difficult and G. molesta has produced resistance to various types of insecticide (Kanga et al., 2003; Ahn et al., 2012; Sarker and Lim, 2018). Disruption of adults mating by releasing pheromone, is a useful management method but with high costs (Wang et al., 2017). Thus, it has become urgent to develop alternative management strategies. To pass the winter, G. molesta enters diapause at the fifth-instar larval stage for about five months (He et al., 2013). Whether the diapausing larvae can successfully get through winter, significantly affects the population dynamics in the following year (He et al., 2013). Previous researches have shown that several neuropeptides play key regulatory roles in diapause, such as DpH. Agonists of DpH can prevent the onset of the protective state of diapause, inducing the pest to commit a form of “ecological suicide” (Nachman, 2014). Thus, development of a control strategy for G. molesta based on neuropeptides is very promising.

To achieve novel insecticidal solutions, identification and characterization of neuroendocrine-related genes by multi-omics approaches have been employed as the primary step in the “genome-to‑lead” strategy (Meyer et al., 2012; Lavore et al., 2018). For G. molesta, which does not have a sequenced genome, insufficient transcriptomic resources are currently available, limiting the progress in control techniques. Therefore, here, RNA sequencing was performed to produce a CNS de novo transcriptome. From the transcriptomic data obtained, 57 neuropeptide precursor genes and 41 neuropeptide GPCR genes were identified. Using a well-established in silico workflow (Chang et al., 2018), 128 mature peptide sequences were predicted from these precursors, and the presence of some of these mature peptides or precursor-related peptides were confirmed by liquid chromatography-tandem mass spectrometry approach. Subsequently, the spatial expression patterns of these 98 genes were performed using quantitative real-time PCR (qRT-PCR). Our results lay a solid foundation for further pharmacological, biochemical, and molecular researches.