CAREER: From Molecules to Mates: Deciphering the Language of Pheromone Communication in Insects

Insects act as harmful pests that spread disease, but they are also vital for growing crops. Because of this, insects deeply affect human health and wealth. Many insects find their mates using airborne chemical signals called pheromones. These signals are often unique to a single species, and insects need them to reproduce. Blocking these chemical signals is a promising way to manage insect populations. Rather than using broad bug sprays, disrupting their mating is precise and safe for the environment. Scientists do not fully understand how insects sense these mating chemicals. However, a better understanding of this process will help us build new tools to control pests on a large scale. This CAREER project will explore the details of chemical communication from atoms to behavior, focusing on insects that are harmful to farming and logging. The long-term goal is to design new chemicals that can boost, block, or confuse mating signals in target species. The project will also bring this research into the classroom by creating learning activities and online resources. These tools will improve science and artificial intelligence literacy and prepare students for jobs in biology and biotechnology. Overall, this work supports the nation by advancing chemistry, biotechnology and neuroscience, and it creates new ways to protect American farming and ecosystems. This project advances NSF’s priorities in Biotechnology, Advanced Manufacturing and Artificial Intelligence. The goal of this research is to elucidate the structural and cellular basis of chemical specificity in insect pheromone receptors, focusing on moths and fruit flies of agricultural relevance. Aim 1 will determine how lepidopteran (moth) pheromone receptors achieve high chemical specificity for pheromones exhibiting only subtle variations in functional group, unsaturation position, or stereochemistry. To accomplish this, cryogenic electron microscopy (cryo-EM) will be used to solve high-resolution structures of selected pheromone-bound receptor complexes, with structure-derived atomic hypotheses subsequently validated through targeted mutagenesis and comprehensive functional assays. Electrophysiological recordings, which provide temporal information, will be used to evaluate how divergent pheromone chemistries modulate receptor activation and inactivation kinetics. Concurrently, structure-guided chemical design will facilitate engineering of novel modulators targeting the receptor binding pocket, and their efficacy in disrupting pheromone tracking will be quantified using in vivo behavioral assays. Aim 2 will focus on Drosophilids, which include fruit flies of agricultural importance. This aim will interrogate how accessory proteins within pheromone sensory neurons orchestrate ligand delivery and turnover. Electrophysiology, live-cell fluorescence imaging assays, and biochemical measurements will be used to evaluate the role of critical components of pheromone sensing neurons: the pheromone-binding protein LUSH and the membrane protein SNMP1. Biochemical and biophysical tools including native-tissue pull-downs, co-immunoprecipitation, and high-speed atomic force microscopy will probe transient protein-protein interactions between SNMP1 and pheromone receptor complexes in membranes. Together, these studies will yield a complete mechanistic model of insect pheromone sensing, establish validated molecular targets and generate chemical strategies for selective, behavior-based management of agricultural pests. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria. NSF Award ID: 2542982 | Program: 01003031DB NSF RESEARCH & RELATED ACTIVIT,01002627DB NSF RESEARCH & RELATED ACTIVIT | Principal Investigator: Josefina del Marmol | Institution: Harvard University, CAMBRIDGE, MA | Award Amount: $1,143,741 View on NSF Award Search: https://www.nsf.gov/awardsearch/show-award/?AWD_ID=2542982 View on Research.gov: https://www.research.gov/awardapi-service/v1/awards/2542982.html