Literature DB >> 23463015

Identification of olfactory volatiles using gas chromatography-multi-unit recordings (GCMR) in the insect antennal lobe.

Kelsey J R P Byers1, Elischa Sanders, Jeffrey A Riffell.   

Abstract

All organisms inhabit a world full of sensory stimuli that determine their behavioral and physiological response to their environment. Olfaction is especially important in insects, which use their olfactory systems to respond to, and discriminate amongst, complex odor stimuli. These odors elicit behaviors that mediate processes such as reproduction and habitat selection(1-3). Additionally, chemical sensing by insects mediates behaviors that are highly significant for agriculture and human health, including pollination(4-6), herbivory of food crops(7), and transmission of disease(8,9). Identification of olfactory signals and their role in insect behavior is thus important for understanding both ecological processes and human food resources and well-being. To date, the identification of volatiles that drive insect behavior has been difficult and often tedious. Current techniques include gas chromatography-coupled electroantennogram recording (GC-EAG), and gas chromatography-coupled single sensillum recordings (GC-SSR)(10-12). These techniques proved to be vital in the identification of bioactive compounds. We have developed a method that uses gas chromatography coupled to multi-channel electrophysiological recordings (termed 'GCMR') from neurons in the antennal lobe (AL; the insect's primary olfactory center)(13,14). This state-of-the-art technique allows us to probe how odor information is represented in the insect brain. Moreover, because neural responses to odors at this level of olfactory processing are highly sensitive owing to the degree of convergence of the antenna's receptor neurons into AL neurons, AL recordings will allow the detection of active constituents of natural odors efficiently and with high sensitivity. Here we describe GCMR and give an example of its use. Several general steps are involved in the detection of bioactive volatiles and insect response. Volatiles first need to be collected from sources of interest (in this example we use flowers from the genus Mimulus (Phyrmaceae)) and characterized as needed using standard GC-MS techniques(14-16). Insects are prepared for study using minimal dissection, after which a recording electrode is inserted into the antennal lobe and multi-channel neural recording begins. Post-processing of the neural data then reveals which particular odorants cause significant neural responses by the insect nervous system. Although the example we present here is specific to pollination studies, GCMR can be expanded to a wide range of study organisms and volatile sources. For instance, this method can be used in the identification of odorants attracting or repelling vector insects and crop pests. Moreover, GCMR can also be used to identify attractants for beneficial insects, such as pollinators. The technique may be expanded to non-insect subjects as well.

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Year:  2013        PMID: 23463015      PMCID: PMC3622093          DOI: 10.3791/4381

Source DB:  PubMed          Journal:  J Vis Exp        ISSN: 1940-087X            Impact factor:   1.355


  20 in total

1.  Representation of natural stimuli in the rodent main olfactory bulb.

Authors:  Da Yu Lin; Stephen D Shea; Lawrence C Katz
Journal:  Neuron       Date:  2006-06-15       Impact factor: 17.173

2.  Neural representation of olfactory mixtures in the honeybee antennal lobe.

Authors:  Nina Deisig; Martin Giurfa; Harald Lachnit; Jean-Christophe Sandoz
Journal:  Eur J Neurosci       Date:  2006-08       Impact factor: 3.386

3.  Electrophysiological measurements from a moth olfactory system.

Authors:  Zainulabeuddin Syed; Walter S Leal
Journal:  J Vis Exp       Date:  2011-03-29       Impact factor: 1.355

4.  Herbivore-induced blueberry volatiles and intra-plant signaling.

Authors:  Cesar R Rodriguez-Saona
Journal:  J Vis Exp       Date:  2011-12-18       Impact factor: 1.355

5.  Characterization and coding of behaviorally significant odor mixtures.

Authors:  Jeffrey A Riffell; Hong Lei; Thomas A Christensen; John G Hildebrand
Journal:  Curr Biol       Date:  2009-02-24       Impact factor: 10.834

6.  Neural correlates of behavior in the moth Manduca sexta in response to complex odors.

Authors:  Jeffrey A Riffell; H Lei; John G Hildebrand
Journal:  Proc Natl Acad Sci U S A       Date:  2009-11-11       Impact factor: 11.205

7.  Acute olfactory response of Culex mosquitoes to a human- and bird-derived attractant.

Authors:  Zainulabeuddin Syed; Walter S Leal
Journal:  Proc Natl Acad Sci U S A       Date:  2009-10-26       Impact factor: 11.205

8.  Neuroethology of oviposition behavior in the moth Manduca sexta.

Authors:  Carolina E Reisenman; Jeffrey A Riffell; John G Hildebrand
Journal:  Ann N Y Acad Sci       Date:  2009-07       Impact factor: 5.691

9.  Behavioral consequences of innate preferences and olfactory learning in hawkmoth-flower interactions.

Authors:  Jeffrey A Riffell; Ruben Alarcón; Leif Abrell; Goggy Davidowitz; Judith L Bronstein; John G Hildebrand
Journal:  Proc Natl Acad Sci U S A       Date:  2008-02-27       Impact factor: 11.205

10.  Spiking patterns and their functional implications in the antennal lobe of the tobacco hornworm Manduca sexta.

Authors:  Hong Lei; Carolina E Reisenman; Caroline H Wilson; Prasad Gabbur; John G Hildebrand
Journal:  PLoS One       Date:  2011-08-29       Impact factor: 3.240

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  2 in total

1.  Three floral volatiles contribute to differential pollinator attraction in monkeyflowers (Mimulus).

Authors:  Kelsey J R P Byers; H D Bradshaw; Jeffrey A Riffell
Journal:  J Exp Biol       Date:  2013-11-06       Impact factor: 3.312

2.  Simultaneous long-term recordings at two neuronal processing stages in behaving honeybees.

Authors:  Martin Fritz Brill; Maren Reuter; Wolfgang Rössler; Martin Fritz Strube-Bloss
Journal:  J Vis Exp       Date:  2014-07-21       Impact factor: 1.355

  2 in total

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