Human Scent Detection and Discrimination by Mosquitoes as a Means for the Design of Bio-Inspired Volatile Detection Systems

Abstract

The PI will characterize human scent volatiles - Chemical analytical methods for characterizing volatiles from humans typically takes hours to days of sample collection and analysis time, and rely on a baseline identification of volatiles from an individual. By contrast, mosquitoes and canines are able to recognize humans from other mammals, and discriminate between individuals, often in short, sub-second, timescales. The fast and accurate sampling of scent information is important because these animals are navigating in a turbulent plume, where the volatile information is dynamically fluctuating in both space and time .The PI will combine chemical and electrophysiological approaches to identify the components (odorant binding proteins; neural circuits) that provide detection and discrimination of human scent by mosquitoes - Mosquitoes are ideal models for examining how olfactory information drives odor recognition and search behaviors. Besides having an extremely sensitive olfactory system, the mosquito is a crepuscular insect that navigates to odor plumes under low-light conditions. Mosquitoes also discriminate between humans based on their volatile cues. The mosquito olfactory system has evolved for sensing human- emitted volatiles through odorant binding proteins (OBPs), that capture specific volatiles from the air (thus serving as a pre-concentration step), and sensitive antennal receptors and neural circuits in the antennal lobe that are wired to increase the signal-noise ratio of the specific chemical signal.The PI will design an artificial antennal lobe that allows detecting these volatiles at trace levels -

Document Details

Document Type
DoD Grant Award
Publication Date
Jul 15, 2016
Source ID
FA95501610167

Entities

People

  • Jeffrey A. Riffell

Organizations

  • Air Force Office of Scientific Research
  • United States Air Force
  • University of Washington

Tags

Fields of Study

  • Biology

Readers

  • Analytical Chemistry
  • Computer Vision.
  • Vector-Borne Disease and Entomology

Technology Areas

  • Space
  • Space - Space Objects