Browse
Submit Data
Databases
API
Help

Dataset Information

10 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Reverse chemical ecology in a moth: machine learning on odorant receptors identifies new behaviorally active agonists.

ABSTRACT: The concept of reverse chemical ecology (exploitation of molecular knowledge for chemical ecology) has recently emerged in conservation biology and human health. Here, we extend this concept to crop protection. Targeting odorant receptors from a crop pest insect, the noctuid moth Spodoptera littoralis, we demonstrate that reverse chemical ecology has the potential to accelerate the discovery of novel crop pest insect attractants and repellents. Using machine learning, we first predicted novel natural ligands for two odorant receptors, SlitOR24 and 25. Then, electrophysiological validation proved in silico predictions to be highly sensitive, as 93% and 67% of predicted agonists triggered a response in Drosophila olfactory neurons expressing SlitOR24 and SlitOR25, respectively, despite a lack of specificity. Last, when tested in Y-maze behavioral assays, the most active novel ligands of the receptors were attractive to caterpillars. This work provides a template for rational design of new eco-friendly semiochemicals to manage crop pest populations.

SUBMITTER: Caballero-Vidal G

PROVIDER: S-EPMC8558168 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Machine learning decodes chemical features to identify novel agonists of a moth odorant receptor.

Project description:Odorant receptors expressed at the peripheral olfactory organs are key proteins for animal volatile sensing. Although they determine the odor space of a given species, their functional characterization is a long process and remains limited. To date, machine learning virtual screening has been used to predict new ligands for such receptors in both mammals and insects, using chemical features of known ligands. In insects, such approach is yet limited to Diptera, whereas insect odorant receptors are known to be highly divergent between orders. Here, we extend this strategy to a Lepidoptera receptor, SlitOR25, involved in the recognition of attractive odorants in the crop pest Spodoptera littoralis larvae. Virtual screening of 3 million molecules predicted 32 purchasable ones whose function has been systematically tested on SlitOR25, revealing 11 novel agonists with a success rate of 28%. Our results show that Support Vector Machine optimizes the discovery of novel agonists and expands the chemical space of a Lepidoptera OR. More, it opens up structure-function relationship analyses through a comparison of the agonist chemical structures. This proof-of-concept in a crop pest could ultimately enable the identification of OR agonists or antagonists, capable of modifying olfactory behaviors in a context of biocontrol.

| S-EPMC6997167 | biostudies-literature

Computational reverse chemical ecology: virtual screening and predicting behaviorally active semiochemicals for Bactrocera dorsalis.

Project description:BackgroundSemiochemical is a generic term used for a chemical substance that influences the behaviour of an organism. It is a common term used in the field of chemical ecology to encompass pheromones, allomones, kairomones, attractants and repellents. Insects have mastered the art of using semiochemicals as communication signals and rely on them to find mates, host or habitat. This dependency of insects on semiochemicals has allowed chemical ecologists to develop environment friendly pest management strategies. However, discovering semiochemicals is a laborious process that involves a plethora of behavioural and analytical techniques, making it expansively time consuming. Recently, reverse chemical ecology approach using odorant binding proteins (OBPs) as target for elucidating behaviourally active compounds is gaining eminence. In this scenario, we describe a "computational reverse chemical ecology" approach for rapid screening of potential semiochemicals.ResultsWe illustrate the high prediction accuracy of our computational method. We screened 25 semiochemicals for their binding potential to a GOBP of B. dorsalis using molecular docking (in silico) and molecular dynamics. Parallely, compounds were subjected to fluorescent quenching assays (Experimental). The correlation between in silico and experimental data were significant (r2 = 0.9408; P < 0.0001). Further, predicted compounds were subjected to behavioral bioassays and were found to be highly attractive to insects.ConclusionsThe present study provides a unique methodology for rapid screening and predicting behaviorally active semiochemicals. This methodology may be developed as a viable approach for prospecting active semiochemicals for pest control, which otherwise is a laborious process.

| S-EPMC4003815 | biostudies-literature

Agonists of G-Protein-Coupled Odorant Receptors Are Predicted from Chemical Features.

Project description:Predicting the activity of chemicals for a given odorant receptor is a longstanding challenge. Here the activity of 258 chemicals on the human G-protein-coupled odorant receptor (OR)51E1, also known as prostate-specific G-protein-coupled receptor 2 (PSGR2), was virtually screened by machine learning using 4884 chemical descriptors as input. A systematic control by functional in vitro assays revealed that a support vector machine algorithm accurately predicted the activity of a screened library. It allowed us to identify two novel agonists in vitro for OR51E1. The transferability of the protocol was assessed on OR1A1, OR2W1, and MOR256-3 odorant receptors, and, in each case, novel agonists were identified with a hit rate of 39-50%. We further show how ligands' efficacy is encoded into residues within OR51E1 cavity using a molecular modeling protocol. Our approach allows widening the chemical spaces associated with odorant receptors. This machine-learning protocol based on chemical features thus represents an efficient tool for screening ligands for G-protein-coupled odorant receptors that modulate non-olfactory functions or, upon combinatorial activation, give rise to our sense of smell.

| S-EPMC7294703 | biostudies-literature

Reverse Chemical Ecology Suggests Putative Primate Pheromones.

Project description:Pheromonal communication is widespread among living organisms, but in apes and particularly in humans there is currently no strong evidence for such phenomenon. Among primates, lemurs use pheromones to communicate within members of the same species, whereas in some monkeys such capabilities seem to be lost. Chemical communication in humans appears to be impaired by the lack or malfunctioning of biochemical tools and anatomical structures mediating detection of pheromones. Here, we report on a pheromone-carrier protein (SAL) adopting a "reverse chemical ecology" approach to get insights on the structures of potential pheromones in a representative species of lemurs (Microcebus murinus) known to use pheromones, Old-World monkeys (Cercocebus atys) for which chemical communication has been observed, and humans (Homo sapiens), where pheromones and chemical communication are still questioned. We have expressed the SAL orthologous proteins of these primate species, after reconstructing the gene encoding the human SAL, which is disrupted due to a single base mutation preventing its translation into RNA. Ligand-binding experiments with the recombinant SALs revealed macrocyclic ketones and lactones as the best ligands for all three proteins, suggesting cyclopentadecanone, pentadecanolide, and closely related compounds as the best candidates for potential pheromones. Such hypothesis agrees with the presence of a chemical very similar to hexadecanolide in the gland secretions of Mandrillus sphinx, a species closely related to C. atys. Our results indicate that the function of this carrier protein has not changed much during evolution from lemurs to humans, although its physiological role has been certainly impaired in humans.

| S-EPMC8789041 | biostudies-literature

Identification of agonists for a group of human odorant receptors.

Project description:Olfaction plays a critical role in several aspects of the human life. Odorants are detected by hundreds of odorant receptors (ORs) which belong to the superfamily of G protein-coupled receptors. These receptors are expressed in the olfactory sensory neurons of the nose. The information provided by the activation of different combinations of ORs in the nose is transmitted to the brain, leading to odorant perception and emotional and behavioral responses. There are ~400 intact human ORs, and to date only a small percentage of these receptors (~10%) have known agonists. The determination of the specificity of the human ORs will contribute to a better understanding of how odorants are discriminated by the olfactory system. In this work, we aimed to identify human specific ORs, that is, ORs that are present in humans but absent from other species, and their corresponding agonists. To do this, we first selected 22 OR gene sequences from the human genome with no counterparts in the mouse, rat or dog genomes. Then we used a heterologous expression system to screen a subset of these human ORs against a panel of odorants of biological relevance, including foodborne aroma volatiles. We found that different types of odorants are able to activate some of these previously uncharacterized human ORs.

| S-EPMC4347425 | biostudies-literature

A reverse chemical ecology approach to explore wood natural durability.

Project description:The natural durability of wood species, defined as their inherent resistance to wood-destroying agents, is a complex phenomenon depending on many biotic and abiotic factors. Besides the presence of recalcitrant polymers, the presence of compounds with antimicrobial properties is known to be important to explain wood durability. Based on the advancement in our understanding of fungal detoxification systems, a reverse chemical ecology approach was proposed to explore wood natural durability using fungal glutathione transferases. A set of six glutathione transferases from the white-rot Trametes versicolor were used as targets to test wood extracts from seventeen French Guiana neotropical species. Fluorescent thermal shift assays quantified interactions between fungal glutathione transferases and these extracts. From these data, a model combining this approach and wood density significantly predicts the wood natural durability of the species tested previously using long-term soil bed tests. Overall, our findings confirm that detoxification systems could be used to explore the chemical environment encountered by wood-decaying fungi and also wood natural durability.

| S-EPMC7415366 | biostudies-literature

Odorant Receptors of the New Zealand Endemic Leafroller Moth Species Planotortrix octo and P. excessana.

Project description:Moths use their sense of smell to find food sources, mating partners and oviposition sites. For this they possess a family of odorant receptors (ORs). Some ORs are used by both sexes whereas others have sex-specific roles. For example, male moths possess ORs specifically tuned to sex pheromones produced by conspecific females. Here we identify sets of ORs from the antennae of New Zealand endemic leafroller moths Planotortrix octo (48 ORs) and P. excessana (47 ORs) using an RNA-Seq approach. Two orthologous ORs show male-biased expression in the adult antennae of both species (OR7 and OR30) and one other OR in each species was female-biased in its expression (PoctOR25, PexcOR14) by qPCR. PAML analysis conducted on male-biased ORs indicated positive selection acting on the male-biased OR7. The fact that OR7 is likely under positive selection, that it is male-biased in its expression and that its orthologue in C. obliquana, CoblOR7, responds to sex pheromone components also utilised by Planotortrix species, suggests that this receptor may also be important in sex pheromone reception in Planotortrix species.

| S-EPMC4803216 | biostudies-literature

Use of machine learning to identify novel, behaviorally active antagonists of the insect odorant receptor co-receptor (Orco) subunit.

Project description:Olfaction is a key component of the multimodal approach used by mosquitoes to target and feed on humans, spreading various diseases. Current repellents have drawbacks, necessitating development of more effective agents. In addition to variable odorant specificity subunits, all insect odorant receptors (ORs) contain a conserved odorant receptor co-receptor (Orco) subunit which is an attractive target for repellent development. Orco directed antagonists allosterically inhibit odorant activation of ORs and we previously showed that an airborne Orco antagonist could inhibit insect olfactory behavior. Here, we identify novel, volatile Orco antagonists. We functionally screened 83 structurally diverse compounds against Orco from Anopheles gambiae. Results were used for training machine learning models to rank probable activity of a library of 1280 odorant molecules. Functional testing of a representative subset of predicted active compounds revealed enrichment for Orco antagonists, many structurally distinct from previously known Orco antagonists. Novel Orco antagonist 2-tert-butyl-6-methylphenol (BMP) inhibited odorant responses in electroantennogram and single sensillum recordings in adult Drosophila melanogaster and inhibited OR-mediated olfactory behavior in D. melanogaster larvae. Structure-activity analysis of BMP analogs identified compounds with improved potency. Our results provide a new approach to the discovery of behaviorally active Orco antagonists for eventual use as insect repellents/confusants.

| S-EPMC6411751 | biostudies-literature

Characterization of Odorant Receptors from a Non-ditrysian Moth, Eriocrania semipurpurella Sheds Light on the Origin of Sex Pheromone Receptors in Lepidoptera.

Project description:Pheromone receptors (PRs) are essential in moths to detect sex pheromones for mate finding. However, it remains unknown from which ancestral proteins these specialized receptors arose. The oldest lineages of moths, so-called non-ditrysian moths, use short-chain pheromone components, secondary alcohols, or ketones, so called Type 0 pheromones that are similar to many common plant volatiles. It is, therefore, possible that receptors for these ancestral pheromones evolved from receptors detecting plant volatiles. Hence, we identified the odorant receptors (ORs) from a non-ditrysian moth, Eriocrania semipurpurella (Eriocraniidae, Lepidoptera), and performed functional characterization of ORs using HEK293 cells. We report the first receptors that respond to Type 0 pheromone compounds; EsemOR3 displayed highest sensitivity toward (2S, 6Z)-6-nonen-2-ol, whereas EsemOR5 was most sensitive to the behavioral antagonist (Z)-6-nonen-2-one. These receptors also respond to plant volatiles of similar chemical structures, but with lower sensitivity. Phylogenetically, EsemOR3 and EsemOR5 group with a plant volatile-responding receptor from the tortricid moth Epiphyas postvittana (EposOR3), which together reside outside the previously defined lepidopteran PR clade that contains the PRs from more derived lepidopteran families. In addition, one receptor (EsemOR1) that falls at the base of the lepidopteran PR clade, responded specifically to β-caryophyllene and not to any other additional plant or pheromone compounds. Our results suggest that PRs for Type 0 pheromones have evolved from ORs that detect structurally-related plant volatiles. They are unrelated to PRs detecting pheromones in more derived Lepidoptera, which, in turn, also independently may have evolved a novel function from ORs detecting plant volatiles.

| S-EPMC5850608 | biostudies-literature

Molecular profiling of activated olfactory neurons identifies odorant receptors for odors in vivo

Project description:We present a high-throughput in vivo method to identify odorant receptors responding to odorants, using phosphorylated ribosome immunoprecipitation of mRNA from olfactory epithelium of odor-stimulated mice followed by RNA-Seq. pS6-IP RNA-Seq in odor stimulated vs control mice olfactory epithelium

2015-08-24 | E-GEOD-59324 | biostudies-arrayexpress

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data