Transcriptional variation and divergence of host-finding behaviour in Steinernema carpocapsae infective juveniles

Behavioral and molecular response of the insect parasitic nematode Steinernema carpocapsae to plant volatiles

Entomopathogenic nematodes (EPNs) use the chemical cues emitted by insects and insect-damaged plants to locate their hosts. Steinernema carpocapsae, a species of EPN, is an established biocontrol agent used against insect pests. Despite its promising potential, the molecular mechanisms underlying its ability to detect plant volatiles remain poorly understood. In this study, we investigated the response of S. carpocapsae infective juveniles (IJs) to 8 different plant volatiles. Among these, carvone was found to be the most attractive volatile compound. To understand the molecular basis of the response of IJs to carvone, we used RNA-Seq technology to identify gene expression changes in response to carvone treatment. Transcriptome analysis revealed 721 differentially expressed genes (DEGs) between carvone-treated and control groups, with 403 genes being significantly upregulated and 318 genes downregulated. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis showed that the responsive DEGs to carvone attraction were mainly involved in locomotion, localization, behavior, response to stimulus, and olfactory transduction. We also identified four upregulated genes of chemoreceptor and response to stimulus that were involved in the response of IJs to carvone attraction. Our results provide insights into the potential transcriptional mechanisms underlying the response of S. carpocapsae to carvone, which can be utilized to develop environmentally friendly strategies for attracting EPNs.

Automated scoring of nematode nictation on a textured background

Entomopathogenic nematodes, including Steinernema spp., play an increasingly important role as biological alternatives to chemical pesticides. The infective juveniles of these worms use nictation-a behavior in which animals stand on their tails-as a host-seeking strategy. The developmentally-equivalent dauer larvae of the free-living nematode Caenorhabditis elegans also nictate, but as a means of phoresy or "hitching a ride" to a new food source. Advanced genetic and experimental tools have been developed for C. elegans, but time-consuming manual scoring of nictation slows efforts to understand this behavior, and the textured substrates required for nictation can frustrate traditional machine vision segmentation algorithms. Here we present a Mask R-CNN-based tracker capable of segmenting C. elegans dauers and S. carpocapsae infective juveniles on a textured background suitable for nictation, and a machine learning pipeline that scores nictation behavior. We use our system to show that the nictation propensity of C. elegans from high-density liquid cultures largely mirrors their development into dauers, and to quantify nictation in S. carpocapsae infective juveniles in the presence of a potential host. This system is an improvement upon existing intensity-based tracking algorithms and human scoring which can facilitate large-scale studies of nictation and potentially other nematode behaviors.

Automated scoring of nematode nictation on a textured background

Entomopathogenic nematodes including Steinernema spp. play an increasingly important role as biological alternatives to chemical pesticides. The infective juveniles of these worms use nictation - a behavior in which animals stand on their tails - as a host-seeking strategy. The developmentally-equivalent dauer larvae of the free-living nematode Caenorhabditis elegans also nictate, but as a means of phoresy or "hitching a ride" to a new food source. Advanced genetic and experimental tools have been developed for C. elegans , but time-consuming manual scoring of nictation slows efforts to understand this behavior, and the textured substrates required for nictation can frustrate traditional machine vision segmentation algorithms. Here we present a Mask R-CNN-based tracker capable of segmenting C. elegans dauers and S. carpocapsae infective juveniles on a textured background suitable for nictation, and a machine learning pipeline that scores nictation behavior. We use our system to show that the nictation propensity of C. elegans from high-density liquid cultures largely mirrors their development into dauers, and to quantify nictation in S. carpocapsae infective juveniles in the presence of a potential host. This system is an improvement upon existing intensity-based tracking algorithms and human scoring which can facilitate large-scale studies of nictation and potentially other nematode behaviors.

Mass Spectrometry-Driven Discovery of Neuropeptides Mediating Nictation Behavior of Nematodes

Neuropeptides regulate animal physiology and behavior, making them widely studied targets of functional genetics research. While the field often relies on differential -omics approaches to build hypotheses, no such method exists for neuropeptidomics. It would nonetheless be valuable for studying behaviors suspected to be regulated by neuropeptides, especially when little information is otherwise available. This includes nictation, a phoretic strategy of Caenorhabditis elegans dauers that parallels host-finding strategies of infective juveniles of many pathogenic nematodes. We here developed a targeted peptidomics method for the model organism C. elegans and show that 161 quantified neuropeptides are more abundant in its dauer stage compared with L3 juveniles. Many of these have orthologs in the commercially relevant pathogenic nematode Steinernema carpocapsae, in whose infective juveniles, we identified 126 neuropeptides in total. Through further behavioral genetics experiments, we identify flp-7 and flp-11 as novel regulators of nictation. Our work advances knowledge on the genetics of nictation behavior and adds comparative neuropeptidomics as a tool to functional genetics workflows.