Stephan Shuichi Haupt

A single sex pheromone receptor determines chemical response specificity of sexual behavior in the silkmoth Bombyx mori.

In insects and other animals, intraspecific communication between individuals of the opposite sex is mediated in part by chemical signals called sex pheromones. In most moth species, male moths rely heavily on species-specific sex pheromones emitted by female moths to identify and orient towards an appropriate mating partner among a large number of sympatric insect species. The silkmoth, Bombyx mori, utilizes the simplest possible pheromone system, in which a single pheromone component, (E, Z)-10,12-hexadecadienol (bombykol), is sufficient to elicit full sexual behavior. We have previously shown that the sex pheromone receptor BmOR1 mediates specific detection of bombykol in the antennae of male silkmoths. However, it is unclear whether the sex pheromone receptor is the minimally sufficient determination factor that triggers initiation of orientation behavior towards a potential mate. Using transgenic silkmoths expressing the sex pheromone receptor PxOR1 of the diamondback moth Plutella xylostella in BmOR1-expressing neurons, we show that the selectivity of the sex pheromone receptor determines the chemical response specificity of sexual behavior in the silkmoth. Bombykol receptor neurons expressing PxOR1 responded to its specific ligand, (Z)-11-hexadecenal (Z11-16:Ald), in a dose-dependent manner. Male moths expressing PxOR1 exhibited typical pheromone orientation behavior and copulation attempts in response to Z11-16:Ald and to females of P. xylostella. Transformation of the bombykol receptor neurons had no effect on their projections in the antennal lobe. These results indicate that activation of bombykol receptor neurons alone is sufficient to trigger full sexual behavior. Thus, a single gene defines behavioral selectivity in sex pheromone communication in the silkmoth. Our findings show that a single molecular determinant can not only function as a modulator of behavior but also as an all-or-nothing initiator of a complex species-specific behavioral sequence.

Pheromone responsiveness threshold depends on temporal integration by antennal lobe projection neurons

Significance The olfactory system of male moths exhibits the ability to detect minute amounts of sex pheromones. How this extreme sensitivity is achieved remains unclear. Using optogenetic techniques to activate a pheromone-responsive olfactory receptor neuron, our results reveal that weak olfactory inputs, but not strong inputs, are temporally integrated in second-order projection neurons to promote behavioral responsiveness. Furthermore, temporal integration of strong olfactory inputs is inhibited by GABAergic mechanisms, indicating that GABA signaling suppresses the amplification of strong stimuli. The timescale of this temporal integration corresponds well to the temporal dynamics of odor signals in the natural environment, suggesting that the olfactory systems of male moths use this mechanism to detect weak pheromone signals in the air. The olfactory system of male moths has an extreme sensitivity with the capability to detect and recognize conspecific pheromones dispersed and greatly diluted in the air. Just 170 molecules of the silkmoth (Bombyx mori) sex pheromone bombykol are sufficient to induce sexual behavior in the male. However, it is still unclear how the sensitivity of olfactory receptor neurons (ORNs) is relayed through the brain to generate high behavioral responsiveness. Here, we show that ORN activity that is subthreshold in terms of behavior can be amplified to suprathreshold levels by temporal integration in antennal lobe projection neurons (PNs) if occurring within a specific time window. To control ORN inputs with high temporal resolution, channelrhodopsin-2 was genetically introduced into bombykol-responsive ORNs. Temporal integration in PNs was only observed for weak inputs, but not for strong inputs. Pharmacological dissection revealed that GABAergic mechanisms inhibit temporal integration of strong inputs, showing that GABA signaling regulates PN responses in a stimulus-dependent fashion. Our results show that boosting of the PNs’ responses by temporal integration of olfactory information occurs specifically near the behavioral threshold, effectively defining the lower bound for behavioral responsiveness.

Ca2+ imaging of identifiable neurons labeled by electroporation in insect brains.

Identifiable neurons in the silkmoth brain were studied physiologically after loading of Ca2+ indicator by local electroporation. Small groups of neurons with projections in confined regions of the antennal lobe were labeled, and Ca2+ imaging showed differences in the dose–response characteristics between projection neurons of the macroglomerular complex that responded to different pheromone components. Compared with projection neurons, local interneurons showed shorter response latencies. Targeted labeling of neurons innervating restricted regions of neuropil by local electroporation is a powerful method that will be generally useful for elucidating details of the functional circuitry in insect brains.

Odorant Concentration Differentiator for Intermittent Olfactory Signals

Animals need to discriminate differences in spatiotemporally distributed sensory signals in terms of quality as well as quantity for generating adaptive behavior. Olfactory signals characterized by odor identity and concentration are intermittently distributed in the environment. From these intervals of stimulation, animals process odorant concentration to localize partners or food sources. Although concentration–response characteristics in olfactory neurons have traditionally been investigated using single stimulus pulses, their behavior under intermittent stimulus regimens remains largely elusive. Using the silkmoth (Bombyx mori) pheromone processing system, a simple and behaviorally well-defined model for olfaction, we investigated the neuronal representation of odorant concentration upon intermittent stimulation in the naturally occurring range. To the first stimulus in a series, the responses of antennal lobe (AL) projection neurons (PNs) showed a concentration dependence as previously shown in many olfactory systems. However, PN response amplitudes dynamically changed upon exposure to intermittent stimuli of the same odorant concentration and settled to a constant, largely concentration-independent level. As a result, PN responses emphasized odorant concentration changes rather than encoding absolute concentration in pulse trains of stimuli. Olfactory receptor neurons did not contribute to this response transformation which was due to long-lasting inhibition affecting PNs in the AL. Simulations confirmed that inhibition also provides advantages when stimuli have naturalistic properties. The primary olfactory center thus functions as an odorant concentration differentiator to efficiently detect concentration changes, thereby improving odorant source orientation over a wide concentration range.

Development of a scheme and tools to construct a standard moth brain for neural network simulations

Understanding the neural mechanisms for sensing environmental information and controlling behavior in natural environments is a principal aim in neuroscience. One approach towards this goal is rebuilding neural systems by simulation. Despite their relatively simple brains compared with those of mammals, insects are capable of processing various sensory signals and generating adaptive behavior. Nevertheless, our global understanding at network system level is limited by experimental constraints. Simulations are very effective for investigating neural mechanisms when integrating both experimental data and hypotheses. However, it is still very difficult to construct a computational model at the whole brain level owing to the enormous number and complexity of the neurons. We focus on a unique behavior of the silkmoth to investigate neural mechanisms of sensory processing and behavioral control. Standard brains are used to consolidate experimental results and generate new insights through integration. In this study, we constructed a silkmoth standard brain and brain image, in which we registered segmented neuropil regions and neurons. Our original software tools for segmentation of neurons from confocal images, KNEWRiTE, and the registration module for segmented data, NeuroRegister, are shown to be very effective in neuronal registration for computational neuroscience studies.

Postsynaptic odorant concentration dependent inhibition controls temporal properties of spike responses of projection neurons in the moth antennal lobe

Although odorant concentration-response characteristics of olfactory neurons have been widely investigated in a variety of animal species, the effect of odorant concentration on neural processing at circuit level is still poorly understood. Using calcium imaging in the silkmoth (Bombyx mori) pheromone processing circuit of the antennal lobe (AL), we studied the effect of odorant concentration on second-order projection neuron (PN) responses. While PN calcium responses of dendrites showed monotonic increases with odorant concentration, calcium responses of somata showed decreased responses at higher odorant concentrations due to postsynaptic inhibition. Simultaneous calcium imaging and electrophysiology revealed that calcium responses of PN somata but not dendrites reflect spiking activity. Inhibition shortened spike response duration rather than decreasing peak instantaneous spike frequency (ISF). Local interneurons (LNs) that were specifically activated at high odorant concentrations at which PN responses were suppressed are the putative source of inhibition. Our results imply the existence of an intraglomerular mechanism that preserves time resolution in olfactory processing over a wide odorant concentration range.

Development of standard brain for silkworm moth, Bombyx mori, linked with a neuron database

Address: 1School of Human Science and Environment, University of Hyogo, Himeji, Hyogo 670-0092, Japan, 2Research Center for Advanced Science and Technology, The University of Tokyo, Tokyo, 153-8904, Japan, 3Graduate School of Life and Environmental Sciences, University of Tsukuba, Tsukuba, Ibaraki, 405-8572, Japan and 4College of Information Science and Engineering, Ritsumeikan University, Kusatsu, Shiga, 5258577, Japan