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Bioelectronic noses: a status report Part I
Biosensors
Vol. 13. No. 3-4, pp. 479-493, 1998 © 1998 Elsevier Science S.A. All rights reserved Printed in Great Britain
& Bioelectronics
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Bioelectronic noses: a status report Part It W. G6peP*, Ch. Ziegler ~, H. Breer b, D. Schild ¢, R. Apfelbach d, J. Joerges" & R. Malaka f aUniversit~it Tiibingen, Institut fur Physikalische und Theoretische Chemie, Auf der Morgenstelle 8, 72076 Ttibingen, Germany bUniversitat Hohenheim, Institut fiir Zoophysiologie, Gabenstr. 30, 70599 Stuttgart, Germany cUniversitat GOttingen, Fachbereich Medizin, Physiologisches Institut, Humboldtallee 23, 37073 G0ttingen, Germany aUniversit~it Ttibingen, Zoologisches Institut, Auf der Morgenstelle 28, 72076 TUbingen, Germany ~FU Berlin, FB Biologie, WE 5, KOnigin-Luise-Str. 28-30, 14195 Berlin, Germany tUniversitat Karlsruhe, Institut fur Logik, Komplexit~it und Deduktionssysteme, Am Fasanengarten 5, 76131 Karlsruhe, Germany (Received ; accepted )
Abstract: The present state of the art to record or mimic electronically the human senses of olfaction and taste is characterized. In this part I, an introduction to our present understanding in the development of electronic and bioelectronic noses is given. Finally the natural olfactory system is described in detail. © 1998 Elsevier Science S.A. Published by Elsevier Science S.A.
1. 1.1
INTRODUCTION Scope
Significant progress has been made in the objective electronic registration and processing of information which is gathered subjectively by the human eye, ear, or touch senses. However, the present state of the art to record or to mimic electronically human olfaction and taste senses is characterized by completely inadequate and very preliminary approaches (see, e.g., Craven et al., *To whom correspondence should be addressed: Tel: 07071/29-76904 Fax: 07071/29-5490 Email: [email protected]. tCo-ordinating authors: W. G0pel and Ch. Ziegler, coordinating authors of the biological section: H. Breer and D. Schild. All other authors are contributing authors.
1996; Vodyanoy, 1989; Ohloff, 1990; Pearce, 1996a, b). This has a variety of reasons. As one example, all attempts to compose complex odors by welldefined amounts of a limited number of standard primary odors failed so far. Other reasons are the lack of an 'odorant vector space' and of a direct correlation between chemical structure and odor perception. Genetic differences of an estimated 1000 olfactory receptor genes in humans influence the individual variations in odor perception. Furthermore, every person has unique experience helping to determine how to react to specific chemosensory events. The general sensation of odors in biology not only includes human odor sensation but also the odor sensation of animals in air and in water with their completely different sensitivity and selectivity patterns to detect chemical species in the gas and liquid state. Since we do not know 479
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tronic noses appear to be a promising
details of odor perception in the various animals, the most general definition of a nose is a detection system to sense any molecule in the gas or liquid state. The odor patterns generated by such odorant detector systems evidently depend on their biological and biochemical architecture (see schematic Fig. 1). These also depend on the individual training, learning, and preconditioning of the systems, on the environment, etc. However, many practical applications require a quantitative objective recording of odors, e.g., in quality and process control or in environmental analysis. This task cannot be realized well by an individual biological nose. 1.2
recent attempt to solve this problem by a combined approach, i.e. 'half way' between sensors and instruments of analytical chemistry (see schematic Fig. 2). This approach makes use of established knowledge in materials science to systematically design new sensors with improved performances by preparing controlled atomic, molecular, supramolecular, and biomimetic structures with high stability and reproducibility. It also makes use of rapid developments in electronics to sensitively determine response signals of sensors, and it makes use of the fast growing field of information theory to analyze complex data obtained from many sensors in an array (see, e.g. Vaihinger & G0pel, 1991; G6pel, 1995a, b, 1996a, b; Hierlemann et al., 1996). A principal advantage of electronic noses is, that they cannot only be used for odor characterization, but also for the quantitative determination of concentrations of individual molecules in a complex environment. Consequently, they may be used to advantage to monitor concentrations of toxic molecules which cannot be sensed by the human nose (such as concentrations of CO) or to determine gross parameters (such as amounts of combustible gases, organic solvent molecules, or toxic compounds).
State o f the art
The following approaches aim at fulfilling this task at least in part. (1) One approach, e.g. chosen in the food industries, is olfactometry. Here, the characterization of odors is performed by a panel of several well-trained persons. The procedure includes a careful cross check of individual odor perceptions to achieve some objectivity. (2) Two other approaches are currently chosen by engineers and chemists, i.e., the use of chemical or biochemical sensors (usually cheap and simple) on the one hand and the use of instruments from analytical chemistry (usually expensive and complex) on the other hand (G6pel & Oehme, 1991). Both approaches are, however, often not satisfactory for an odor characterization which is useful for practical applications. As an example, results from individual chemical sensors cannot be used to characterize specific coffee aromas. The same holds for results from gas chromatographs as the most appropriate instruments used by analytical chemists in this context: More than 1500 different individual peaks are typically recorded for only one coffee sample which, however, cannot be correlated at all unequivocally with the specific sensory odor components. Quality or process control in the coffee industry does, however, require to utilize unequivocal correlations between measurable parameters and aromas. (3) Chemical sensor systems also termed elec480
1.3
Trends
Electronic noses are intended to imitate the signal processing in natural noses, although the elementary steps of signal transduction, signal processing, and identification of chemical patterns evidently differ drastically from those realized in the biological nose. In both cases, however, a controlled signal transduction across interfaces
plays the key role. This signal transduction is primarily triggered by odor molecules. It involves the transport of electrons, ions, or molecules, which induce structural modifications with certain time dependent signal patterns at the various stages of the complex information cascade. Progress in the current development of electronic noses on the one side and progress in our understanding of biochemical, molecular, biological, physiological, and behavioral details of odor sensation on the other side make it now possible
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Bioelectronic noses." a status report Part I
Input signal Odor mt
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,=:::>Output signal Granule cell
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Fig. 1. Schematic representation of the signal cascade in the human nose which is involved in recognizing odor molecules (Schweizer-Berberich et al., 1995).
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Modular Sensor Systems Gas Sensing: NO2,NH3,CO, CO2, H20, 02, SO2,CH,, alkanes, PER, VOC's, ... Odors: I coffee, wine, perfume, ... Liquid and biosensing: anti-FMD virus, thrombin inhibitors, atrazin, glucose, lactose, strychnine.... ~
*,(NO=) =(CO)
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~
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Fig. 2. Schematic representation of electronic or (bio-)electronic nose systems which are realized by modular sensor systems. Typical examples for their applications are listed on the left side. A varie~ of different materials (see Table 1 below) is used for adjusting specific recognition sites by coating the transducer. In general, several different transducer principles (see Table 2 below) have to be applied simultaneously to achieve sufficient "chemical orthogonality" of the overall "chemical image". This leads to modular sensor systems as indicated schematically by three arrows at the transducer level (GOpel, 1995a, b, d, Hierlemann et al., 1996; Ulmer et al., 1997),
to outline possible scenarios and characterize milestones f o r the development o f 'bioelectronic noses' as one area of future bioelectronics (GOpel,
the technical and biological sensory systems, (4) to understand similarities and differences of both sensory systems (e.g. 'neural nets' in computer sciences and in nerve systems), and (5) to optimize hybrid systems.
1995c, 1996a, b). The final goal is to bridge the gap between the technical and biological world of odor detection by electronically recording 'chemical images' of any odor environment with high resolution in both, space and time (similar to the existing electronically recorded 'optical images' with their excellent resolution in space and time for selected frequencies of electromagnetic radiation). This goal includes
Table 1 illustrates very schematically the hierarchy in the description of bioelectronic noses with an increasing complexity concerning structures and functions. Details are outlined in the following chapters of this status report which gives a brief survey on
(1) to achieve a basic understanding of structural and functional aspects of natural chemosensory systems including, in particular, their general and subjective learning processes, (2) to monitor parameters which represent directly values of human odor sensation, (3) to design hybrid systems by complementing o r exchanging certain components between
(1) specific highlights in our current understanding of olfaction with natural chemosensory systems (subsystems indicated in italics in Table 1, chapter 2), (2) current and future research and development of electronic and bioelectronic noses (Part II, chapter 1), (3) computer science aspects of odor recognition (Part II, chapter 2), and
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TABLE 1 Molecular hierarchy in the complexity of structures and functions which may be used in the design of (bio-)electronic noses (G6pel, in press) • inorganic structures and organic molecules ebiomimetic recognition sites ebiological recognition sites odorant binding proteins olfactory receptors • recognition sites embedded in biological membranes olfactory receptors in cilia • recognition sites in membranes with subsequent signal amplification ewhole cells olfactory cells • cell arrays eneural tissue olfactory mucosa • neural tissue with subsequent signal processing step olfactory mucosa and olfactory bulb ebrain olfactory mucosa, olfactory bulb, and olfactory cortex •animals ehumans odor sensation of distinguished test persons
(4) conclusions (Part II, chapter 3). Part II will be published in B i o s e n s o r s & Bioelectronics, Vol. 13(4). The report contains selected contributions from several specialists in informatics, physics, physical chemistry, organic chemistry, biochemistry, biology, medicine, and behavioral sciences who presented their ideas at a workshop on 'Bioelectronic Noses' in Berlin (Germany) in October 1996 (see Appendix).
2. O L F A C T I O N W I T H N A T U R A L C H E M O S E N S O R Y SYSTEMS Our sense of smell is able to recognize and discriminate, with great sensitivity and accuracy, thousands of volatile molecules of diverse structure. Even stereoisomeric compounds are discriminated. Odorant stimuli at concentrations as low as a few parts per trillion are detected. The perception threshold for, e.g., acetic acid, lies at 5 × 1013 molecules/cm 3 air. However, many animals show much lower detection limits, e.g. 5 × 105 molecules acetic acid per cm 3 air for dogs (Neuhaus, 1953). These thresholds are constant only over a short range of time and are subject to ontogenetic (Apfelbach et al., 1991), seasonal, and hormonal fluctuations.
In mammals, the olfactory system consists of three main sub-systems, the olfactory mucosa, the olfactory bulb (OB), and central brain areas including the olfactory cortex (OC). The first step of odorant detection is accomplished by specialized chemosensory neurons located in the nasal neuroepithelium; these cells encode the strength, duration, and quality of odorant stimuli into distinct patterns of afferent neuronal signals. Thus, the perception of odors is the result of complex molecular biochemical and physiological reaction cascades. At the end the molecular structure of an odorant is converted into a pattern of neuronal activity.
2.1
Olfactory sensory neurons
Olfactory receptor neurons (ORNs) are small, bipolar neurons. Up to about 20 cilia issue from the top of the unbranched dendrite (compare Fig. 1). In contrast to other neural cells, olfactory receptor cells have a life-time of only a few weeks and are reproduced throughout life from basal cells in the epithelium. The overall responses to natural stimuli of olfactory neurons can be summarized as follows (Getchell, 1986): (1) In the absence of stimuli the neurons show a spontaneous discharge rate. 483
W. Giipel et al. (2) When maximally stimulated with odorants, the neurons respond with about 20 to 30 spikes/s. (3) Responses to natural stimuli show characteristic and well reproducible phasic-tonic response patterns: the spike rate increases within a few seconds to a maximum and then decreases to a fairly constant niveau. (4) Most vertebrate olfactory neurons appear to code the intensity of an odorant only in a small concentration window. Above a threshold concentration c,, a neuron increases its firing rate and reaches a maximum firing rate at a saturation concentration C,,,t, with log(c,,,/c,,) being in the range between 0.5 and 3. This means that many different receptor neurons are necessary to code the intensity of an odorant over the whole concentration range. (5) A typical vertebrate olfactory receptor neuron responds to a large number of stimuli, each of which may lead to a different response spike rate, and a particular stimulus would usually cause different responses in different cells. Most vertebrate olfactory sensory neurons do not seem to be very selective for particular odorants. 2.1.1 Odorant binding proteins The process of olfaction begins when odorous molecules reach the chemosensory epithelium. In contrast to aquatic animals, which smell watersoluble odorants, such as amino acids, which have ready access to the olfactory receptor cells, terrestrial animals smell volatile, primarily lipophilic molecules. These airborne odorants must traverse the aqueous milieu of the mucus layer covering the nasal epithelium before contacting the recognition sites on the olfactory cilia. Small globular proteins in the mucus fluid surrounding the sensory dendrite and cilia, which were found to bind odorous molecules and therefore called odorant binding proteins (OBPs) are supposed to accomodate hydrophobic compounds in the aqueous environment and enhance their access to the receptor sites (Breer et al., 1994; Pelosi, 1994). The recently discovered diversity of OBPs suggests that the different OBPs may be specialized in recognizing and binding distinct classes of odorous compounds; in this way, it is conceivable that OBPs may act as selective filters for hydrophobic molecules approaching the olfactory epithelium. Moreover, it has been hypothesized that 484
Biosensors & Bioelectronics OBPs may play a dual role, shuttling the odorous molecules to the appropriate receptors and in addition as a co-initiator of the signalling process. This mode of action would be reminescent to the function of soluble binding proteins in the periplasmic space of bacteria, where e.g. maltosebinding protein changes conformation upon interaction with maltose and the complex then activates the receptor in the plasma membrane. The notion that distinct OBPs may be able to discriminate between classes of hydrophobic molecules render these proteins interesting recognition molecules. The question whether interaction of OBPs with appropriate hydrophobic ligands elicits conformational changes of these globular proteins and whether these changes could be picked up by microelectronic devices awaits experimental support. 2.1.2
Olfitctor 3, receptors
Structural features. Once an odorant has passed the mucus interface, it binds to receptor proteins within the membrane of cilia or microvilli of olfactory neurons. The long search for olfactory receptors has led to the discovery of a novel multigene family in rat that encodes membrane proteins with seven transmembrane-spanning domains and are expressed in olfactory sensory neurons (Buck & Axel, 1991) (Fig. 3). These receptors exhibit the characteristic structural features of the superfamily of G-protein-coupled receptors. In mammals, the repertoire of olfactory receptors is extremely large and may consist of as many as thousand different subtypes (Buck & Axel, 1991; Raining et al., 1993). The extent and pattern of diversity among the receptor proteins encoded by the multigene family suggest that they may be capable of binding a large variety of structurally diverse odorants. Meanwhile, putative odorant receptors from a variety of mammalian species have been identified. Comparing their primary structures and putative membrane topology with other members of the G-protein-coupled receptor superfamily revealed minimal intra- and extracellular loop structures. Furthermore, certain structural features appear to be unique for odorant receptors, most notably the high degree of sequence variability in central transmembrane domains which are supposed to form the ligand binding site of the receptor. The variability of this region is thought to reflect the diversity of binding sites with different specificity. The
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Bioelectronic noses: a status report Part I
Bmbrane
Lne
Intracellular loop Fig. 3. Membrane topology of odor receptor proteins.
observation, that based on structural similarities, receptor types can be categorized into different groups has led to the concept that receptors sharing pronounced sequence identity with each other may recognize similar odorants whereas receptors with more divergent sequences may be tuned to structurally unrelated odorants. Comparative aspects. Comparative studies of lower vertebrate revealed that fish also have a gene family that encodes receptor proteins with some homology to rat odorant receptors; however, the size of the fish receptor repertoire appears to be considerably smaller than in mammals (Ngai et al., 1993; Weth et al., 1996). Amphibia possess a gene repertoire encoding two distinct classes of olfactory receptors: one class related to receptors of fish and one class similar to receptors of mammals. Sequence comparison indicates that the fish-like receptors represent closely related mem-
bers of only two subfamilies, whereas mammalian-like receptors are more distantly related, most of them representing a different subfamily. The fish-like receptor genes are exclusively expressed in the lateral diverticulum of the frog's nose, specialized for detecting water-soluble odorants, whereas mammalian-like receptors are expressed in sensory neurons of the main diverticulum, responsible for the reception of volatile odors (Freitag et al., 1995). Topographic expression patterns. Extensive in situ hybridization studies in different mammalian
species have revealed that odorant receptors are widely scattered within the sensory surface, but not randomly distributed. Sensory neurons expressing distinct receptor types are topographically distributed in one of several rostro-caudal zones (Ressler et al., 1993; Vassar et al., 1993; Strotmann et al., 1994). Recent evidence supports 485
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the concept that sensory cells expressing the same receptor type may project to the same glomerulus in the olfactory bulb (Ressler et al., 1994; Vassar et al., 1994). In the zebrafish, individual odorant receptors seem to be expressed in concentric rings (Weth et al., 1996). When backlabeled from a particular glomerulus olfactory receptor neurons show a distribution similar to the innermost domain of odorant receptor expression, consistent with a 'same specificity-same target' mechanism for olfactory receptor neuron pathfinding.
Functional properties. Expression studies have confirmed that the novel gene family indeed encodes receptor proteins for odorants. It was demonstrated that host cells heterologously expressing receptor proteins responded to submicromolar concentrations of certain odorants with the generation of inositol trisphosphate in a dose-dependent manner. Graded responses to only a subset of odorants out of a collection of odors indicated that distinct receptor types exhibit a selective but relatively broad ligand specificity (Raming et al., 1993). This observation is in line with the concept that olfactory neurons may express only one receptor type but still respond to a variety of different odors. Extending the functional characterization of an array of receptor types may provide some insight in the ligand specificity, the reaction spectrum, of individual olfactory receptors. High level expression may allow large scale production of distinct olfactory receptor proteins; this is an important prerequisite towards the goal using natural receptors as recognition entities in artificial devices. A recent study, which has demonstrated for the first time that overexpression of olfactory receptor proteins in bacterial cells is possible, may be considered as an important step towards this goal. Reconstituted in liposomes, the purified receptor protein apparently gained some of its original tertiary structure and specifically interacted with certain odorants (Kiefer et al., 1996). Thus, the easily manipulated bacterial system may not only allow to perform large-scale screening programs that are required for unraveling the specific interrelationship between the array of olfactory receptor types and the numerous odor ligands, but in addition provide large amounts of receptor proteins suitable to operate as recognition molecules in biosensors.
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Transduction pathways in olfactory
neuroFis
Binding of odorants to ciliar receptor proteins trigger intracellular signal cascades which eventually lead to a receptor potential and spiking of the neuron (Restrepo et al., 1996). Two different transduction pathways seem to be prevailing: The best characterized pathway involves cyclic adenosine monophosphate (cAMP) (Fig. 4). An increase in cAMP concentration elicited in olfactory neurons by some odorants (Breer et al., 1990) causes opening of a non-specific cation conductance go, the channels of which are directly gated by cAMP (Nakamura & Gold, 1987). cAMP-gated channels have been shown to be localized mainly to olfactory cilia. These cAMPgated channels are permeable for Na +, K +, and Ca 2+. The major effect of the activation of gcn is thus to increase [Ca2+]i (Frings et al., 1995), which then acts as a third messenger. An increase in [Ca2+]i elicited by opening of cAMP-gated channels activates ciliary Ca2+-acti vated C1- channels (Kleene & Gesteland, 1991). Ca2+-activated C1- current resulting from this increase in [Ca2+]i is depolarizing because the reversal potential Ec~ for C I is considerably more positive than the resting potential in these neurons (Zhainazarov & Ache, 1995). The current through the C1- channels thus gives rise to a depolarizing receptor potential, which may initiate the generation of action potentials. The second olfactory transduction pathway appears to be mediated by phospholipase C, inositol 1,4,5-trisphosphate (IP3) and [Ca 2+] (Fig. 5). First, some odorants lead, via a receptor and a phospholipase C, to an increase in IP3 (Boekhoff et al., 1990; Breer et al., 1990). Second, olfactory neurons of Xenopus laevis responded to dialysis of IP3 from the patch pipette with activation of two different current components: a calcium current and a non-specific cation conductance (Schild et al., 1995). The ionic properties of this Ca 2+dependent non-specific cation conductance suggest that g,.,, is identical with the non-specific cation conductance stimulated by dialysis of IP3 into the cytoplasm of Xenopus olfactory neurons. There is little doubt that the resulting current leads to depolarizing receptor potentials and the initiation of action potentials. Recently, the increase in [Ca2+]i has been reported to gate a Ca2+-activated K + conductance, which would be hyperpolarizing (Morales et al., 1995). The stimulation of second messenger for-
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Bioelectronic noses: a status report Part I
Na ÷
C a 2÷
CI
Fig. 4. Schematic representation o f the signal transduction cascade in ciliary membranes of olfactory sensory neurons. For further explanations, see text.
mation in olfactory neurons can thus lead to depolarization or hyperpolarization depending upon which second messenger regulated conductances are activated in a given neuron. A depolarizing response would tend to increase action potential firing rate (excitation), while a hyperpolarizing response would tend to suppress the basal rate of firing of olfactory neurons (inhibition). In addition, if both depolarizing and hyperpolarizing pathways exist in the same cell, as is the case in olfactory neurons from various species (Fadool & Ache, 1992; Kang & Caprio, 1995), a single olfactory neuron could integrate the two signals. Differential stimulation or suppression of different olfactory neurons by different odors could be used by the olfactory system as a mechanism for contrast enhancement allowing the system to differentiate between closely related odorants. 2.1.4
Electrical signalling in olfactory neurons
The odor-induced current loads the cell's capacitance and depolarizes the membrane potential from the resting potential of about -85 mV to the cell's firing threshold. Due to their high resting impedance (about 10 GI~), olfactory receptor cells are extremely sensitive and generate action potentials upon depolarizing currents of only a few pA: with R -- 10GI~, a current of 5 p A would lead to a depolarization of AU = 10 GI).5 pA = 50 mV. The depolarization activates voltage-gated
conductances of the receptor neurons. There seem to be two voltage-gated inward currents and three different outward currents (Schild, 1989): (i) a voltage-gated Na + current of the Hodgkin-Huxley type, responsible for the initiation of action potentials; (ii) a small L-type Ca 2+ current; (iii) a Ca 2+dependent K+-current IK~c,); (iv) a fast inactivating K+-current Ix~. that inactivates within less than a second, and (v) a small K+-current IK~ of the delayed rectifier type. In some species there seems to be a low-threshold Ca2+-current which could speed up the receptor potential. The physiological role of the outward conductances can be imagined as follows: gKs is the predominant, though very small conductance at rest. It is responsible for the high impedance, a correspondingly high sensitivity, and the resting membrane potential, gKi activates at about -30 mV and contributes to the repolarization of action potentials, gK~ca) is activated by membrane voltage, but also by Ca 2+ ions that enter the cell through Ca 2+ channels during action potentials. Therefore, in addition to participating in the repolarization of action potentials, gK~ca) lowers the plasma membrane's impedance as long as the intracellular concentration of free Ca 2+, [Ca2+]i, stays elevated. The higher the cell's activity, the higher is [Ca2+] i, and the more activated is gKtca). This decreases the neuron's sensitivity to odorants as a function of its recent activity. 487
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odorants
1. messenger
2. messenger
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gca,cat .9
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receptor potentials Fig. 5. Signalling cascades in olfi~ctory receptor neurons. For details, see text.
2.2
Olfactory bulb and higher brain centers
When the olfactory system is stimulated with odorants, the temporal response patterns of olfactory bulb neurons are complex (Mori, 1987). Expectedly, they are also correlated with the respiratory rhythm (Chaput et al., 1992). A typical mitral cell responds differentially to a large number of odorants. Simultaneous recordings with two electrodes from two mitral cells have shown that the responses are positively correlated if the cells are in direct neighborhood to each other. In a certain range beyond this neighborhood, the correlation is negative (Chaput, 1990). Adjacent mitral cells or mitral cells within a certain neighborhood are thus responsive in a similar way to a given stimulus (Mori et al., 1992). A more detailed picture of the olfactory bulb (OB) activity during odor application has emerged from optical recordings. The OB was stained 488
with voltage-sensitive dyes, the absorbance or fluorescence of which reflect the voltages across the plasma membrane of the stained ceils. The optical signals were registered by a video camera or by an array of photodiodes. These methods have excellent time resolution and at the same time a fairly high spatial resolution. They clearly show that (i) different odor stimuli lead to different activation patterns, (ii) waves of activity spread over the OB when odorants are applied to the nose, and (iii) large areas of the OB are involved in the neuronal representation of odorants (Kauer, 1991). The representation of odorants must thus be understood as a rapid sequence of images somewhat like a movie. The zebrafish olfactory bulb contains only about 80 glomeruli, of which more than a quarter (possibly most) have stereotyped positions and are identifiable from animal to animal (Baier & Korsching, 1994). Therefore the response to a
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particular odorant is expected to show a broad, albeit not random distribution in the sensory epithelium, and a more localized response in the olfactory bulb. Individual amino acids (which are olfactory stimuli for fish) can be distinguished unambiguously, based on their spatial response patterns. In the rat and the frog the signals from the receptor cell axons to mitral/tufted cells are transmitted by glutamate via NMDA and AMPA receptors (Berkowicz et al., 1994), because EPSPs of mitral cells upon electrical stimulation of the olfactory nerve can be blocked by blockers of NMDA and AMPA channels. Many synapses between mitral cells and interneurons are of the reciprocal type, i.e., bidirectional chemical synapses, at which glutamate (and possibly N-acetylaspartylglutamate: NAAG) activates NMDA and AMPA channels of interneurons, which, in turn, release GABA and gate GABAA channels on the mitral cell side of the synapse. This feedback inhibition is, however, suppressed at active reciprocal synapses via metabotropic glutamate receptors (Bischofsberger & Schild, 1996), so that mitral cells supposedly mediate very little negative feedback upon themselves. They rather induce inhibition of neighboring mitral cells via interneurons. The function of reciprocal synapses in the olfactory bulb appears thus to be an inputdependent lateral inhibition. Further, norepinephrine, released by axon terminals and varicosities of efferent fibers originating in the locus ceruleus, acts at the mitral cell side of reciprocal synapses by blocking N-type Ca 2÷ channels thereby reducing the release of glutamate. This modulatory influence of the brainstem eventually leads to a disinhibition of mitral cells (Trombley & Shepherd, 1992; Trombley, 1992). This might enhance the OB responses to odorants and/or influence olfactory learning. Another interesting question of olfactory signal processing is the representation of odor m i x t u r e s at the level of the olfactory bulb or the olfactory lobe, the analogon of the olfactory bulb in insects. This problem has recently been studied in the olfactory lobe of the honey bee (Fig. 6) (Joerges et al., 1997; Malaka et al., 1995). The design of 'bioelectronic noses' will require devices that can process, analyze, and classify the complex sensory signals in such a way that accurate identification of odors over a wide range of concentrations and against noisy backgrounds will be possible. Therefore the internal representations of
Bioelectronic noses: a status report Part 1
odors have to be investigated. Optically recorded spatial activity patterns evoked by different odors and mixtures are odor specific and distributed. The responses to natural plant extracts (which are complex blends with dozens to hundreds of components) are not fundamentally different from those of pure substances. Fig. 7 shows as one example the activity patterns that are evoked by the stimuli citral alone or hexanol alone. The pattern produced by the mixture of these odorants is - on the first approximation - a combination of both single component patterns. But comparing it to the arithmetic sum of the two single patterns shows that some differences exist: One glomerulus is activated less than by citral alone (marked with triangle), indicating an inhibitory interaction between hexanol and citral for this site. Another site is activated stronger than predicted by the sum (marked with star), indicating synergistic mixture effects. Thus, the mixture evokes a pattern that is a nonlinear combination of the single component patterns. These results indicate that nonlinear network interactions (mainly through inhibitory interneurons) help the brain to form unique internal representations for complex natural odor blends. Unfortunately, relatively little is known about the central processing of olfactory stimuli. The neurons of the projection areas of the olfactory tract in the CNS have been studied very little with electrophysiological or biochemical techniques, so that there is presently no coherent view of their function. The precise relationships between higher olfactory signal processing and behavior are therefore currently not understood. Little is also known about other cortical regions that might be involved in the processing of olfactory information. Results obtained by positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) show that in addition to the bilateral increase of cerebral blood flow in the piriform cortex, the insular cortex and the right orbitofrontal cortex are also activated by odorous stimulation (Zatorre et al., 1992). In magnetoencephalographic studies brain areas can be identified that generate olfactory bioresponses in humans (Kettenmann et al., subm.). Bilateral activation was observed in the temporal lobes and parts of the insular cortex at different latencies during the first second after olfactory stimulation by vanillin and hydrogen sulfide. Apart from the known primary olfactory areas these 489
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Fig. 6. Olfactoo' senso~ system o f insect." sensoo, cells are located in the antennae projecting into distinct glomeruli of the antennal lobe. Distinct odors elicit responses in specific regions of the lobe. For details of the latter, see Fig. 7.
A
B
Citral
C
Hexanol
D
Mixture
Fig. 7. (A) Antennal lobe o f the honeybee (computer reconstruction from 50 confocal thin sections of an antennal lobe preparation) (B) and (C) Spatial activity patterns for citral and hexanol in one animal. View of the antennal lobe (250 txrn x 250 txrn). Dark color: strong activity; white: no activity. (D) Activity pattern evoked by the mixture of citral and hexanol. For details, see text.
secondary areas could be differentiated with respect to the hedonic properties of the odorants.
UNLINKED REFERENCES G6pel, in press Kettenmann et al., submitted 490
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in the zebra fish form an invariant pattern and are identifiable across animals. J. Neurosci. 14, 219-230. Berkowicz, D. A., Trombley, P. Q. and Shepherd, G. M. (1994) Evidence for glutamate as the olfactory receptor cell neurotransmitter. J. Neurophysiol. 1994, 2557-2561. Bischofsberger, J. and Schild, D. (1996) Glutamate and N-acetyl-aspartyl-glutamate block HVA calcium currents in frog olfactory bulb interneurons via an mGluR2/3-1ike receptor. J. Neurophysiol. 76, 2089-2092. Boekhoff, I., Tareilus, E., Strotmann, J. and Breer, H. (1990) Rapid activation of alternative second messenger pathways in olfactory cilia from rats by different odorants. EMBO J. 9, 2453-2458. Breer, H., Raming, K. and Krieger, J. (1994) Signal recognition and transduction in olfactory neurons. Biochim. Biophys. Acta 1224, 277-287. Breer, H., Boekhoff, I. and Tareilus, E. (1990) Rapid kinetics of second messenger formation in olfactory transduction. Nature 344, 65-68. Buck, L. and Axel, R. (1991) A novel multigene family may encode odorant receptors: a molecular basis for odor recognition. Cell 65, 175-187. Chaput, M.A., Is the olfactory bulb functionally organized in parallel columns?! In: Chemosensory information processing, ed. D. Schild. Springer, Berlin, 1990, pp. 247-257. Chaput, M. A., Buonviso, N. and Berthommier, F. (1992) Temporal patterns in spontaneous and odour-evoked mitral cell discharges recorded in anaesthetized freely breathing animals. Eur. J. Neurosci. 4, 813-822. Craven, M. A., Gardner, J. W. and Bartlett, P. N. (1996) Electronic noses - development and future prospects. Trends in Analytical Chemistry 15, 486493. Fadool, D. A. and Ache, B. W. (1992) Plasma membrane inositol 1,4,5-triphosphate-activated channels mediate signal transduction in lobster olfactory receptor neurons. Neuron 9, 907-918. Freitag, J., Krieger, J., Strotmann, J. and Breer, H. (1995) Two classes of olfactory receptors in Xenopus laevis. Neuron 15, 1383-1392. Frings, S., Seifert, R., Godde, M. and Kaupp, U. B. (1995) Profoundly different calcium permeation and blockage determine the specific function of distinct cyclic-nucleotide-gated channels. Neuron 15, 169-179. Getchell, T. V. (1986) Functional properties of vertebrate olfactory receptor neurons. Physiol. Rev. 66, 772-818. G6pel, W. and Oehme, M., Chemical Sensors and Instrumentation in Analytical Chemistry. In Sensors: A Comprehensive Survey, Chemical and Biochemical Sensor, Vol. 3, ed. W. G6pel, J. Hesse
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and J.N. Zemel. VCH, Weinheim (FRG), 1991, pp. 819-846. G6pel, W., Sensors and 'Smart' Molecular Nanostructures: Components for Future Information Technologies. In Sensors: A Comprehensive Survey, Vol. 8, ed. Trends in Sensor Technology/Sensor Marketed. W. G6pel, J. Hesse and J.N. Zemel. VCH, Weinheim, 1995a, pp. 295-336 GOpel, W. (1995b) Supramolecular and Polymeric Structures for Gas Sensors. Sensors and Actuators B 24-25, 17-32. G6pel, W. (1995c) Interface Analysis in Biosensor Design. Biosensors and Bioelectronics 10, 853883. G6pel, W., Basic Principles and New Trends in the Development of Chemical Sensors for Domestic Applications. In: Sensors for Domestic, ed. A. D'Amico and G. Sberveglieri, World Scientific, Singapore, 1995, p. 49-57. G6pel, W. (1996a) Ultimate Limits in the Miniaturization of Chemical Sensors. Sensors and Actuators A 56, 83-102. G6pel, W. (1996b) Nanosensors and Molecular Recognition. Nanotechnology, Spec. Issue of Microelectronics Engineering 32, 75-110. G6pel, W., Bioelectronics and Nanotechnologies. Biosensors and Bioelectronics, in press. Hierlemann, A., Schweizer-Berberich, M., Weimar, U., Kraus, G., Pfau, A. and GOpel, W., Pattern Recognition and Multicomponent Analysis. In: Sensors Update Sensor Technology - Applications - Markets, Vol. 2, ed. H. Baltes, W. G6pel and J. Hesse. VCH, Weinheim (FRG), 1996, pp. 119-180. Joerges, J., Ktittner, A., Galizia, G. and Menzel, R. (1997) Representations of odours and odour mixtures visualized in the honeybee brain. Nature 387, 285-288. Kang, J. S. and Caprio, J. (1995) Electrophysiological responses of single olfactory bulb neurons to amino acids in the channel catfish, Ictalurus punctatus. J. Neurophysiol. 74, 1421-1434. Kauer, J. S. (1991) Contributions of topography and parallel processing to odor coding in the vertebrate olfactory pathway. TINS 14, 79-85. Kettenmann, B., Hummel, C., Stefan, H. and Kobal, G., Multiple olfactory activity in the human neocortex identified by magnetic source imaging, (submitted). Kiefer, H., Krieger, J., Olszewski, J. D., Von Heijne, G., Prestwich, G. D. and Breer, H. (1996) Expression of an olfactory receptor in Escherichia coli: Purification, reconstitution, and ligand binding. Biochemistry 35, 16077-16084. Kleene, S. J. and Gesteland, R. C. (1991) Calciumactivated chloride conductance in frog olfactory cilia. J. Neurosci. 11, 3624-3629. Malaka, R., Ragg, T. and Hammer, M. (1995) Kinetic models of odor transduction implemented as arti491
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ficial neural networks - Simulations of complex response properties of honeybee olfactory neurons. Biol. Cybern. 73, 195-207. Morales, B., Labarca, P. and Bacigalupo, J. (1995) A ciliary K + conductance sensitive to charibdotoxin underlies inhibitory responses in toad olfactory receptor neurons. FEBS Lett. 359, 41-44. Mori, K. (1987) Membrane and synaptic properties of identified neurons in the olfactory bulb. Progr. Neurobiol. 29, 275-320. Mori, K., Mataga, N. and Imamura, K. (1992) Differential specificities of single mitral cells in rabbit olfactory bulb for a homologous series of fatty acid odor molecules. J. Neurophysiol. 67, 786-789. Nakamura, T. and Gold, G. H. (1987) A cyclic nucleotide-gated conductance in olfactory receptor cilia. Nature 325, 442-444. Neuhaus, W. (1953) Uber die Riechsch~irfe des Hundes ftir Fettsfiuren. Z. vergl. Physiol. 35, 527-552. Ngai, J., Chess, A., Dowling, M. M., Necles, N., Macagno, E. R. and Axel, R. (1993) Coding of olfactory information: topography of odorant receptor expression in the catfish olfactory epithelium. Cell 72, 1-20. Ohloff, G., Riechstoffe und Geruchssinn: Die molekulare Welt der Dtifte. Springer, Berlin, 1990. Pearce, T. C. (1996a) Computational parallels between the biological olfactory pathway and its analogue 'The Electronic Nose': Part I. Biological Olfaction. BioSystems 41, 4 3 ~ 7 . Pearce, T. C. (1996b) Computational parallels between the biological olfactory pathway and its analogue 'The Electronic Nose': Part II. Sensor-based machine olfaction. BioSystems 41, 69-90. Pelosi, P. (1994) Odorant binding proteins. Crit. Rev. Biochem. Molec. Biol. 29, 199-228. Raming, K., Krieger, J., Strotmann, J., Boekhoff, I., Kubick, S., Baumstark, C. and Breer, H. (1993) Cloning and expression of odorant recpetors. Nature 361, 353-356. Ressler, K. J., Sullivan, S. L. and Buck, L. B. (1993) A zonal organization of odorant receptor gene expression in the olfactory epithelium. Cell 73, 597-609. Ressler, K. J., Sullivan, S. L. and Buck, L. B. (1994) Information coding in the olfactory system: evidence for a stereotyped and highly organized epitope map in the olfactory bulb. Cell 79, 12451255. Restrepo, D., Teeter, J. H. and Schild, D. (1996) Second messenger signaling in olfactory transduction. J. Neurobiol. 30, 3 7 4 8 . Schild, D. (1989) Whole-cell currents in olfactory receptor cells of Xenopus laevis. Exp. Brain Res. 78, 223-232. Schild, D., Lischka, F. W. and Restrepo, D. (1995) InsP3 causes an increase in apical [Ca2+]~ by activ492
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ating two distinct components in vertebrate olfactory receptor cells. J. Neurophysiol. 73, 862-866. Schweizer-Berberich, M., Harsch, A. and G6pel, W. (1995) Wie menschlich sind elektronische Nasen?. Technisches Messen 62, 237-249. Strotmann, J., Wanner, I., Helfrich, T., Beck, A. and Breer, H. (1994) Rostro-caudal patterning of receptor-expressing olfactory neurons in the rat nasal cavity. Cell Tissue Res. 278, 11-20. Trombley, P. Q. (1992) Norepinephrine inhibits calcium currents and epsps via a G-protein-coupled mechanism in olfactory bulb neurons. J. Neurosci. 12, 3992-3998. Trombley, P. Q. and Shepherd, G. M. (1992) Noradrenergic inhibition of synaptic transmission between mitral and granule cells in mammalian olfactory bulb cultures. J. Neurosci. 12, 39853991. Ulmer, H., Mitrovics, J., Noetzel, G., Weimar, U. and G6pel, W. (1997) Odours and Flavours Identified with Hybrid Modular Sensor Systems. Sensors and Actuators, B43, 24-33. Vaihinger, S. and G6pel, W., Multi-Component Analysis in Chemical Sensing. In: Sensors: A Comprehensive Survey, Chemical and Biochemical Sensor, Vol. 2, ed. W. G6pel, J. Hesse and J.N. Zemel. VCH, Weinheim (FRG), 1991, pp. 191-237. Vassar, R., Ngai, J. and Axel, R. (1993) Spatial segregation of odorant receptor expression in the mammalian olfactory epithelium. Cell 74, 309-318. Vassar, R., Chao, S. K., Sitcheran, R., Nunez, J. M., Vosshall, L. B. and Axel, R. (1994) Topographic organization of sensory projection to the olfactory bulb. Cell 79, 961-991. Vodyanoy, V., Molecular sensors based on olfactory transduction. In: Molecular Electronics: Biosensors and Biocomputers, ed. F.T. Hong. Plenum Press, New York, 1989, pp. 317-328. Weth, F., Nadler, W. and Korsching, S. (1996) Nested expression domains for odorant receptors in zebrafish olfactory epithelium. Proc. Natl. Acad. Sci. USA 93, 13321-13326. Zatorre, R. J., Jones-Gotman, M., Evans, A. C. and Meyer, E. (1992) Functional localization of lateralization of human olfactory cortex. Nature 360, 339-340. Zhainazarov, A. B. and Ache, B. W. (1995) Odorinduced currents in Xenopus olfactory receptor cells measured with perforated-patch recording. J. Neurophysiol. 74, 479-483.
APPENDIX Presentations at the W o r k s h o p "Bioelectronic
Noses
Odor and Molecular Recognition",
Berlin, 18. and 19.10.1996
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Organizer: Dr. A. Hache (Projekttrager Biologie, Energie, Okologie des BMBF, Berlin
INTRODUCTION Biological Aspects of odor reception (J. Boeckh, University of Regensburg, D) Bioelectronic Aspects of molecular recognition (W. Gt~pel, University of Ttibingen, D)
ODOR SENSATION AND MOLECULAR RECOGNITION IN ANIMALS Complex signal processing of olfactory signals: the example of cortical representation by means of imaging processing (G. Kobal, University of Erlangen, D) Lectines and their influence on olfactory reception of vertebrates (R. Apfelbach, University of Ttibingen, D) Functional reconstitution of olfactory systems (H. Hatt, University of Bochum, D) Olfactory coding in the nerve systems of insects (J. Joerges, R. Malaka, Universities of Karlsruhe and Berlin, D
Bioelectronic noses: a status report Part 1
CELLS AND CELL ARRAYS IN VITRO FOR DETECTING ODORS AND FOR MOLECULAR RECOGNITION Electronic signal recording from neuronal tissues: Retina as a case study (H. H~immerle, Natural and Medical Sciences Institute, Reutlingen, D) Molecular recognition with neuronal networks in vitro: extracellular recordings of network signals (Ch. Ziegler, University of Ttibingen, D) Cells on sensors: cellular aspects of neuronal recognition (L. Laxhuber, CellControl Biomedical Laboratories Mtinchen, D)
BIOMIMETIC STRUCTURES FOR ODOR DETECTION AND MOLECULAR RECOGNITION Synthetic receptors based on combinatorial cyclopeptide libraries (G. Jung, University of TUbingen) Synthesis and fine-tuning of macrocyclic oligo-amides and sulfonamides as biomimetic receptor molecules for odor sensors (F. V6gtle, University of Bonn, D)
NEURONAL PROCESSING OF OLFACTORY SIGNALS Data and hypothesis for coding odors at different levels of neuronal organization (J. Boeckh, University of Regensburg, D) Neuronal representation of water soluble odorants in fish (S. Korsching, University of K61n, D) Lectin binding properties of olfactory subsystems of vertebrates (D. L. Meyer, University of GOttingen, D)
BIOMOLECULAR ASPECTS: RECEPTORS; BINDING PROTEINS, AND SIGNAL TRANSDUCTION Receptors and transduction mechanisms of olfactory cells (H. Breer, University of Hohenstein, D) Transduction mechanisms in olfactory cells of frog: Approaches to design bioelectronic sensors (D. Schild, University of G6ttingen, D) Signal generation in visual and odor cells - differences and similarities (U. B. Kaupp, Research Center Jialich (KFA), D)
BIOMIMETIC AND MOLECULAR PATTERN RECOGNITION Molecular, biological and biomimetic systems for signal recognition and signal amplification (H. L. Schmidt, University of WeihenstephanMtinchen, D) Biomimetic, supramolecular, and molecular structures for sensor arrays for molecular pattern recognition (W. G6pel, University of TUbingen, D)
BIOINFORMATIC ASPECTS OF ODOR RECOGNITION Molecular pattern recognition (A. Zell, University of Ttibingen, D) Efficient methods for analyzing high dimensional data (V. Heun, University of Mtinchen, D)
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Bioelectronic noses: a status report Part It W. G6peP*, Ch. Ziegler ~, H. Breer b, D. Schild ¢, R. Apfelbach d, J. Joerges" & R. Malaka f aUniversit~it Tiibingen, Institut fur Physikalische und Theoretische Chemie, Auf der Morgenstelle 8, 72076 Ttibingen, Germany bUniversitat Hohenheim, Institut fiir Zoophysiologie, Gabenstr. 30, 70599 Stuttgart, Germany cUniversitat GOttingen, Fachbereich Medizin, Physiologisches Institut, Humboldtallee 23, 37073 G0ttingen, Germany aUniversit~it Ttibingen, Zoologisches Institut, Auf der Morgenstelle 28, 72076 TUbingen, Germany ~FU Berlin, FB Biologie, WE 5, KOnigin-Luise-Str. 28-30, 14195 Berlin, Germany tUniversitat Karlsruhe, Institut fur Logik, Komplexit~it und Deduktionssysteme, Am Fasanengarten 5, 76131 Karlsruhe, Germany (Received ; accepted )
Abstract: The present state of the art to record or mimic electronically the human senses of olfaction and taste is characterized. In this part I, an introduction to our present understanding in the development of electronic and bioelectronic noses is given. Finally the natural olfactory system is described in detail. © 1998 Elsevier Science S.A. Published by Elsevier Science S.A.
1. 1.1
INTRODUCTION Scope
Significant progress has been made in the objective electronic registration and processing of information which is gathered subjectively by the human eye, ear, or touch senses. However, the present state of the art to record or to mimic electronically human olfaction and taste senses is characterized by completely inadequate and very preliminary approaches (see, e.g., Craven et al., *To whom correspondence should be addressed: Tel: 07071/29-76904 Fax: 07071/29-5490 Email: [email protected]. tCo-ordinating authors: W. G0pel and Ch. Ziegler, coordinating authors of the biological section: H. Breer and D. Schild. All other authors are contributing authors.
1996; Vodyanoy, 1989; Ohloff, 1990; Pearce, 1996a, b). This has a variety of reasons. As one example, all attempts to compose complex odors by welldefined amounts of a limited number of standard primary odors failed so far. Other reasons are the lack of an 'odorant vector space' and of a direct correlation between chemical structure and odor perception. Genetic differences of an estimated 1000 olfactory receptor genes in humans influence the individual variations in odor perception. Furthermore, every person has unique experience helping to determine how to react to specific chemosensory events. The general sensation of odors in biology not only includes human odor sensation but also the odor sensation of animals in air and in water with their completely different sensitivity and selectivity patterns to detect chemical species in the gas and liquid state. Since we do not know 479
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tronic noses appear to be a promising
details of odor perception in the various animals, the most general definition of a nose is a detection system to sense any molecule in the gas or liquid state. The odor patterns generated by such odorant detector systems evidently depend on their biological and biochemical architecture (see schematic Fig. 1). These also depend on the individual training, learning, and preconditioning of the systems, on the environment, etc. However, many practical applications require a quantitative objective recording of odors, e.g., in quality and process control or in environmental analysis. This task cannot be realized well by an individual biological nose. 1.2
recent attempt to solve this problem by a combined approach, i.e. 'half way' between sensors and instruments of analytical chemistry (see schematic Fig. 2). This approach makes use of established knowledge in materials science to systematically design new sensors with improved performances by preparing controlled atomic, molecular, supramolecular, and biomimetic structures with high stability and reproducibility. It also makes use of rapid developments in electronics to sensitively determine response signals of sensors, and it makes use of the fast growing field of information theory to analyze complex data obtained from many sensors in an array (see, e.g. Vaihinger & G0pel, 1991; G6pel, 1995a, b, 1996a, b; Hierlemann et al., 1996). A principal advantage of electronic noses is, that they cannot only be used for odor characterization, but also for the quantitative determination of concentrations of individual molecules in a complex environment. Consequently, they may be used to advantage to monitor concentrations of toxic molecules which cannot be sensed by the human nose (such as concentrations of CO) or to determine gross parameters (such as amounts of combustible gases, organic solvent molecules, or toxic compounds).
State o f the art
The following approaches aim at fulfilling this task at least in part. (1) One approach, e.g. chosen in the food industries, is olfactometry. Here, the characterization of odors is performed by a panel of several well-trained persons. The procedure includes a careful cross check of individual odor perceptions to achieve some objectivity. (2) Two other approaches are currently chosen by engineers and chemists, i.e., the use of chemical or biochemical sensors (usually cheap and simple) on the one hand and the use of instruments from analytical chemistry (usually expensive and complex) on the other hand (G6pel & Oehme, 1991). Both approaches are, however, often not satisfactory for an odor characterization which is useful for practical applications. As an example, results from individual chemical sensors cannot be used to characterize specific coffee aromas. The same holds for results from gas chromatographs as the most appropriate instruments used by analytical chemists in this context: More than 1500 different individual peaks are typically recorded for only one coffee sample which, however, cannot be correlated at all unequivocally with the specific sensory odor components. Quality or process control in the coffee industry does, however, require to utilize unequivocal correlations between measurable parameters and aromas. (3) Chemical sensor systems also termed elec480
1.3
Trends
Electronic noses are intended to imitate the signal processing in natural noses, although the elementary steps of signal transduction, signal processing, and identification of chemical patterns evidently differ drastically from those realized in the biological nose. In both cases, however, a controlled signal transduction across interfaces
plays the key role. This signal transduction is primarily triggered by odor molecules. It involves the transport of electrons, ions, or molecules, which induce structural modifications with certain time dependent signal patterns at the various stages of the complex information cascade. Progress in the current development of electronic noses on the one side and progress in our understanding of biochemical, molecular, biological, physiological, and behavioral details of odor sensation on the other side make it now possible
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Bioelectronic noses." a status report Part I
Input signal Odor mt
~ i ~ # Triggered ",G'TP~ A II" cA~II~i , i oc hna n n e l ,,
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Fig. 1. Schematic representation of the signal cascade in the human nose which is involved in recognizing odor molecules (Schweizer-Berberich et al., 1995).
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Modular Sensor Systems Gas Sensing: NO2,NH3,CO, CO2, H20, 02, SO2,CH,, alkanes, PER, VOC's, ... Odors: I coffee, wine, perfume, ... Liquid and biosensing: anti-FMD virus, thrombin inhibitors, atrazin, glucose, lactose, strychnine.... ~
*,(NO=) =(CO)
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Fig. 2. Schematic representation of electronic or (bio-)electronic nose systems which are realized by modular sensor systems. Typical examples for their applications are listed on the left side. A varie~ of different materials (see Table 1 below) is used for adjusting specific recognition sites by coating the transducer. In general, several different transducer principles (see Table 2 below) have to be applied simultaneously to achieve sufficient "chemical orthogonality" of the overall "chemical image". This leads to modular sensor systems as indicated schematically by three arrows at the transducer level (GOpel, 1995a, b, d, Hierlemann et al., 1996; Ulmer et al., 1997),
to outline possible scenarios and characterize milestones f o r the development o f 'bioelectronic noses' as one area of future bioelectronics (GOpel,
the technical and biological sensory systems, (4) to understand similarities and differences of both sensory systems (e.g. 'neural nets' in computer sciences and in nerve systems), and (5) to optimize hybrid systems.
1995c, 1996a, b). The final goal is to bridge the gap between the technical and biological world of odor detection by electronically recording 'chemical images' of any odor environment with high resolution in both, space and time (similar to the existing electronically recorded 'optical images' with their excellent resolution in space and time for selected frequencies of electromagnetic radiation). This goal includes
Table 1 illustrates very schematically the hierarchy in the description of bioelectronic noses with an increasing complexity concerning structures and functions. Details are outlined in the following chapters of this status report which gives a brief survey on
(1) to achieve a basic understanding of structural and functional aspects of natural chemosensory systems including, in particular, their general and subjective learning processes, (2) to monitor parameters which represent directly values of human odor sensation, (3) to design hybrid systems by complementing o r exchanging certain components between
(1) specific highlights in our current understanding of olfaction with natural chemosensory systems (subsystems indicated in italics in Table 1, chapter 2), (2) current and future research and development of electronic and bioelectronic noses (Part II, chapter 1), (3) computer science aspects of odor recognition (Part II, chapter 2), and
482
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Bioelectronic noses: a status report Part I
TABLE 1 Molecular hierarchy in the complexity of structures and functions which may be used in the design of (bio-)electronic noses (G6pel, in press) • inorganic structures and organic molecules ebiomimetic recognition sites ebiological recognition sites odorant binding proteins olfactory receptors • recognition sites embedded in biological membranes olfactory receptors in cilia • recognition sites in membranes with subsequent signal amplification ewhole cells olfactory cells • cell arrays eneural tissue olfactory mucosa • neural tissue with subsequent signal processing step olfactory mucosa and olfactory bulb ebrain olfactory mucosa, olfactory bulb, and olfactory cortex •animals ehumans odor sensation of distinguished test persons
(4) conclusions (Part II, chapter 3). Part II will be published in B i o s e n s o r s & Bioelectronics, Vol. 13(4). The report contains selected contributions from several specialists in informatics, physics, physical chemistry, organic chemistry, biochemistry, biology, medicine, and behavioral sciences who presented their ideas at a workshop on 'Bioelectronic Noses' in Berlin (Germany) in October 1996 (see Appendix).
2. O L F A C T I O N W I T H N A T U R A L C H E M O S E N S O R Y SYSTEMS Our sense of smell is able to recognize and discriminate, with great sensitivity and accuracy, thousands of volatile molecules of diverse structure. Even stereoisomeric compounds are discriminated. Odorant stimuli at concentrations as low as a few parts per trillion are detected. The perception threshold for, e.g., acetic acid, lies at 5 × 1013 molecules/cm 3 air. However, many animals show much lower detection limits, e.g. 5 × 105 molecules acetic acid per cm 3 air for dogs (Neuhaus, 1953). These thresholds are constant only over a short range of time and are subject to ontogenetic (Apfelbach et al., 1991), seasonal, and hormonal fluctuations.
In mammals, the olfactory system consists of three main sub-systems, the olfactory mucosa, the olfactory bulb (OB), and central brain areas including the olfactory cortex (OC). The first step of odorant detection is accomplished by specialized chemosensory neurons located in the nasal neuroepithelium; these cells encode the strength, duration, and quality of odorant stimuli into distinct patterns of afferent neuronal signals. Thus, the perception of odors is the result of complex molecular biochemical and physiological reaction cascades. At the end the molecular structure of an odorant is converted into a pattern of neuronal activity.
2.1
Olfactory sensory neurons
Olfactory receptor neurons (ORNs) are small, bipolar neurons. Up to about 20 cilia issue from the top of the unbranched dendrite (compare Fig. 1). In contrast to other neural cells, olfactory receptor cells have a life-time of only a few weeks and are reproduced throughout life from basal cells in the epithelium. The overall responses to natural stimuli of olfactory neurons can be summarized as follows (Getchell, 1986): (1) In the absence of stimuli the neurons show a spontaneous discharge rate. 483
W. Giipel et al. (2) When maximally stimulated with odorants, the neurons respond with about 20 to 30 spikes/s. (3) Responses to natural stimuli show characteristic and well reproducible phasic-tonic response patterns: the spike rate increases within a few seconds to a maximum and then decreases to a fairly constant niveau. (4) Most vertebrate olfactory neurons appear to code the intensity of an odorant only in a small concentration window. Above a threshold concentration c,, a neuron increases its firing rate and reaches a maximum firing rate at a saturation concentration C,,,t, with log(c,,,/c,,) being in the range between 0.5 and 3. This means that many different receptor neurons are necessary to code the intensity of an odorant over the whole concentration range. (5) A typical vertebrate olfactory receptor neuron responds to a large number of stimuli, each of which may lead to a different response spike rate, and a particular stimulus would usually cause different responses in different cells. Most vertebrate olfactory sensory neurons do not seem to be very selective for particular odorants. 2.1.1 Odorant binding proteins The process of olfaction begins when odorous molecules reach the chemosensory epithelium. In contrast to aquatic animals, which smell watersoluble odorants, such as amino acids, which have ready access to the olfactory receptor cells, terrestrial animals smell volatile, primarily lipophilic molecules. These airborne odorants must traverse the aqueous milieu of the mucus layer covering the nasal epithelium before contacting the recognition sites on the olfactory cilia. Small globular proteins in the mucus fluid surrounding the sensory dendrite and cilia, which were found to bind odorous molecules and therefore called odorant binding proteins (OBPs) are supposed to accomodate hydrophobic compounds in the aqueous environment and enhance their access to the receptor sites (Breer et al., 1994; Pelosi, 1994). The recently discovered diversity of OBPs suggests that the different OBPs may be specialized in recognizing and binding distinct classes of odorous compounds; in this way, it is conceivable that OBPs may act as selective filters for hydrophobic molecules approaching the olfactory epithelium. Moreover, it has been hypothesized that 484
Biosensors & Bioelectronics OBPs may play a dual role, shuttling the odorous molecules to the appropriate receptors and in addition as a co-initiator of the signalling process. This mode of action would be reminescent to the function of soluble binding proteins in the periplasmic space of bacteria, where e.g. maltosebinding protein changes conformation upon interaction with maltose and the complex then activates the receptor in the plasma membrane. The notion that distinct OBPs may be able to discriminate between classes of hydrophobic molecules render these proteins interesting recognition molecules. The question whether interaction of OBPs with appropriate hydrophobic ligands elicits conformational changes of these globular proteins and whether these changes could be picked up by microelectronic devices awaits experimental support. 2.1.2
Olfitctor 3, receptors
Structural features. Once an odorant has passed the mucus interface, it binds to receptor proteins within the membrane of cilia or microvilli of olfactory neurons. The long search for olfactory receptors has led to the discovery of a novel multigene family in rat that encodes membrane proteins with seven transmembrane-spanning domains and are expressed in olfactory sensory neurons (Buck & Axel, 1991) (Fig. 3). These receptors exhibit the characteristic structural features of the superfamily of G-protein-coupled receptors. In mammals, the repertoire of olfactory receptors is extremely large and may consist of as many as thousand different subtypes (Buck & Axel, 1991; Raining et al., 1993). The extent and pattern of diversity among the receptor proteins encoded by the multigene family suggest that they may be capable of binding a large variety of structurally diverse odorants. Meanwhile, putative odorant receptors from a variety of mammalian species have been identified. Comparing their primary structures and putative membrane topology with other members of the G-protein-coupled receptor superfamily revealed minimal intra- and extracellular loop structures. Furthermore, certain structural features appear to be unique for odorant receptors, most notably the high degree of sequence variability in central transmembrane domains which are supposed to form the ligand binding site of the receptor. The variability of this region is thought to reflect the diversity of binding sites with different specificity. The
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Bioelectronic noses: a status report Part I
Bmbrane
Lne
Intracellular loop Fig. 3. Membrane topology of odor receptor proteins.
observation, that based on structural similarities, receptor types can be categorized into different groups has led to the concept that receptors sharing pronounced sequence identity with each other may recognize similar odorants whereas receptors with more divergent sequences may be tuned to structurally unrelated odorants. Comparative aspects. Comparative studies of lower vertebrate revealed that fish also have a gene family that encodes receptor proteins with some homology to rat odorant receptors; however, the size of the fish receptor repertoire appears to be considerably smaller than in mammals (Ngai et al., 1993; Weth et al., 1996). Amphibia possess a gene repertoire encoding two distinct classes of olfactory receptors: one class related to receptors of fish and one class similar to receptors of mammals. Sequence comparison indicates that the fish-like receptors represent closely related mem-
bers of only two subfamilies, whereas mammalian-like receptors are more distantly related, most of them representing a different subfamily. The fish-like receptor genes are exclusively expressed in the lateral diverticulum of the frog's nose, specialized for detecting water-soluble odorants, whereas mammalian-like receptors are expressed in sensory neurons of the main diverticulum, responsible for the reception of volatile odors (Freitag et al., 1995). Topographic expression patterns. Extensive in situ hybridization studies in different mammalian
species have revealed that odorant receptors are widely scattered within the sensory surface, but not randomly distributed. Sensory neurons expressing distinct receptor types are topographically distributed in one of several rostro-caudal zones (Ressler et al., 1993; Vassar et al., 1993; Strotmann et al., 1994). Recent evidence supports 485
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the concept that sensory cells expressing the same receptor type may project to the same glomerulus in the olfactory bulb (Ressler et al., 1994; Vassar et al., 1994). In the zebrafish, individual odorant receptors seem to be expressed in concentric rings (Weth et al., 1996). When backlabeled from a particular glomerulus olfactory receptor neurons show a distribution similar to the innermost domain of odorant receptor expression, consistent with a 'same specificity-same target' mechanism for olfactory receptor neuron pathfinding.
Functional properties. Expression studies have confirmed that the novel gene family indeed encodes receptor proteins for odorants. It was demonstrated that host cells heterologously expressing receptor proteins responded to submicromolar concentrations of certain odorants with the generation of inositol trisphosphate in a dose-dependent manner. Graded responses to only a subset of odorants out of a collection of odors indicated that distinct receptor types exhibit a selective but relatively broad ligand specificity (Raming et al., 1993). This observation is in line with the concept that olfactory neurons may express only one receptor type but still respond to a variety of different odors. Extending the functional characterization of an array of receptor types may provide some insight in the ligand specificity, the reaction spectrum, of individual olfactory receptors. High level expression may allow large scale production of distinct olfactory receptor proteins; this is an important prerequisite towards the goal using natural receptors as recognition entities in artificial devices. A recent study, which has demonstrated for the first time that overexpression of olfactory receptor proteins in bacterial cells is possible, may be considered as an important step towards this goal. Reconstituted in liposomes, the purified receptor protein apparently gained some of its original tertiary structure and specifically interacted with certain odorants (Kiefer et al., 1996). Thus, the easily manipulated bacterial system may not only allow to perform large-scale screening programs that are required for unraveling the specific interrelationship between the array of olfactory receptor types and the numerous odor ligands, but in addition provide large amounts of receptor proteins suitable to operate as recognition molecules in biosensors.
486
Biosensors & Bioelectronics 2.1.3
Transduction pathways in olfactory
neuroFis
Binding of odorants to ciliar receptor proteins trigger intracellular signal cascades which eventually lead to a receptor potential and spiking of the neuron (Restrepo et al., 1996). Two different transduction pathways seem to be prevailing: The best characterized pathway involves cyclic adenosine monophosphate (cAMP) (Fig. 4). An increase in cAMP concentration elicited in olfactory neurons by some odorants (Breer et al., 1990) causes opening of a non-specific cation conductance go, the channels of which are directly gated by cAMP (Nakamura & Gold, 1987). cAMP-gated channels have been shown to be localized mainly to olfactory cilia. These cAMPgated channels are permeable for Na +, K +, and Ca 2+. The major effect of the activation of gcn is thus to increase [Ca2+]i (Frings et al., 1995), which then acts as a third messenger. An increase in [Ca2+]i elicited by opening of cAMP-gated channels activates ciliary Ca2+-acti vated C1- channels (Kleene & Gesteland, 1991). Ca2+-activated C1- current resulting from this increase in [Ca2+]i is depolarizing because the reversal potential Ec~ for C I is considerably more positive than the resting potential in these neurons (Zhainazarov & Ache, 1995). The current through the C1- channels thus gives rise to a depolarizing receptor potential, which may initiate the generation of action potentials. The second olfactory transduction pathway appears to be mediated by phospholipase C, inositol 1,4,5-trisphosphate (IP3) and [Ca 2+] (Fig. 5). First, some odorants lead, via a receptor and a phospholipase C, to an increase in IP3 (Boekhoff et al., 1990; Breer et al., 1990). Second, olfactory neurons of Xenopus laevis responded to dialysis of IP3 from the patch pipette with activation of two different current components: a calcium current and a non-specific cation conductance (Schild et al., 1995). The ionic properties of this Ca 2+dependent non-specific cation conductance suggest that g,.,, is identical with the non-specific cation conductance stimulated by dialysis of IP3 into the cytoplasm of Xenopus olfactory neurons. There is little doubt that the resulting current leads to depolarizing receptor potentials and the initiation of action potentials. Recently, the increase in [Ca2+]i has been reported to gate a Ca2+-activated K + conductance, which would be hyperpolarizing (Morales et al., 1995). The stimulation of second messenger for-
Biosensors & Bioelectronics
Bioelectronic noses: a status report Part I
Na ÷
C a 2÷
CI
Fig. 4. Schematic representation o f the signal transduction cascade in ciliary membranes of olfactory sensory neurons. For further explanations, see text.
mation in olfactory neurons can thus lead to depolarization or hyperpolarization depending upon which second messenger regulated conductances are activated in a given neuron. A depolarizing response would tend to increase action potential firing rate (excitation), while a hyperpolarizing response would tend to suppress the basal rate of firing of olfactory neurons (inhibition). In addition, if both depolarizing and hyperpolarizing pathways exist in the same cell, as is the case in olfactory neurons from various species (Fadool & Ache, 1992; Kang & Caprio, 1995), a single olfactory neuron could integrate the two signals. Differential stimulation or suppression of different olfactory neurons by different odors could be used by the olfactory system as a mechanism for contrast enhancement allowing the system to differentiate between closely related odorants. 2.1.4
Electrical signalling in olfactory neurons
The odor-induced current loads the cell's capacitance and depolarizes the membrane potential from the resting potential of about -85 mV to the cell's firing threshold. Due to their high resting impedance (about 10 GI~), olfactory receptor cells are extremely sensitive and generate action potentials upon depolarizing currents of only a few pA: with R -- 10GI~, a current of 5 p A would lead to a depolarization of AU = 10 GI).5 pA = 50 mV. The depolarization activates voltage-gated
conductances of the receptor neurons. There seem to be two voltage-gated inward currents and three different outward currents (Schild, 1989): (i) a voltage-gated Na + current of the Hodgkin-Huxley type, responsible for the initiation of action potentials; (ii) a small L-type Ca 2+ current; (iii) a Ca 2+dependent K+-current IK~c,); (iv) a fast inactivating K+-current Ix~. that inactivates within less than a second, and (v) a small K+-current IK~ of the delayed rectifier type. In some species there seems to be a low-threshold Ca2+-current which could speed up the receptor potential. The physiological role of the outward conductances can be imagined as follows: gKs is the predominant, though very small conductance at rest. It is responsible for the high impedance, a correspondingly high sensitivity, and the resting membrane potential, gKi activates at about -30 mV and contributes to the repolarization of action potentials, gK~ca) is activated by membrane voltage, but also by Ca 2+ ions that enter the cell through Ca 2+ channels during action potentials. Therefore, in addition to participating in the repolarization of action potentials, gK~ca) lowers the plasma membrane's impedance as long as the intracellular concentration of free Ca 2+, [Ca2+]i, stays elevated. The higher the cell's activity, the higher is [Ca2+] i, and the more activated is gKtca). This decreases the neuron's sensitivity to odorants as a function of its recent activity. 487
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odorants
1. messenger
2. messenger
l
1
G-protein adenylylcyclase
G-protein PLC
2-.. cAMP
IP3
DAG PKC
gcn
gca,cat .9
???
l 3. messenger
C a 2+
C a 2+
I go(ca)
gcan
gK(ca)
l
receptor potentials Fig. 5. Signalling cascades in olfi~ctory receptor neurons. For details, see text.
2.2
Olfactory bulb and higher brain centers
When the olfactory system is stimulated with odorants, the temporal response patterns of olfactory bulb neurons are complex (Mori, 1987). Expectedly, they are also correlated with the respiratory rhythm (Chaput et al., 1992). A typical mitral cell responds differentially to a large number of odorants. Simultaneous recordings with two electrodes from two mitral cells have shown that the responses are positively correlated if the cells are in direct neighborhood to each other. In a certain range beyond this neighborhood, the correlation is negative (Chaput, 1990). Adjacent mitral cells or mitral cells within a certain neighborhood are thus responsive in a similar way to a given stimulus (Mori et al., 1992). A more detailed picture of the olfactory bulb (OB) activity during odor application has emerged from optical recordings. The OB was stained 488
with voltage-sensitive dyes, the absorbance or fluorescence of which reflect the voltages across the plasma membrane of the stained ceils. The optical signals were registered by a video camera or by an array of photodiodes. These methods have excellent time resolution and at the same time a fairly high spatial resolution. They clearly show that (i) different odor stimuli lead to different activation patterns, (ii) waves of activity spread over the OB when odorants are applied to the nose, and (iii) large areas of the OB are involved in the neuronal representation of odorants (Kauer, 1991). The representation of odorants must thus be understood as a rapid sequence of images somewhat like a movie. The zebrafish olfactory bulb contains only about 80 glomeruli, of which more than a quarter (possibly most) have stereotyped positions and are identifiable from animal to animal (Baier & Korsching, 1994). Therefore the response to a
Biosensors & Bioelectronics
particular odorant is expected to show a broad, albeit not random distribution in the sensory epithelium, and a more localized response in the olfactory bulb. Individual amino acids (which are olfactory stimuli for fish) can be distinguished unambiguously, based on their spatial response patterns. In the rat and the frog the signals from the receptor cell axons to mitral/tufted cells are transmitted by glutamate via NMDA and AMPA receptors (Berkowicz et al., 1994), because EPSPs of mitral cells upon electrical stimulation of the olfactory nerve can be blocked by blockers of NMDA and AMPA channels. Many synapses between mitral cells and interneurons are of the reciprocal type, i.e., bidirectional chemical synapses, at which glutamate (and possibly N-acetylaspartylglutamate: NAAG) activates NMDA and AMPA channels of interneurons, which, in turn, release GABA and gate GABAA channels on the mitral cell side of the synapse. This feedback inhibition is, however, suppressed at active reciprocal synapses via metabotropic glutamate receptors (Bischofsberger & Schild, 1996), so that mitral cells supposedly mediate very little negative feedback upon themselves. They rather induce inhibition of neighboring mitral cells via interneurons. The function of reciprocal synapses in the olfactory bulb appears thus to be an inputdependent lateral inhibition. Further, norepinephrine, released by axon terminals and varicosities of efferent fibers originating in the locus ceruleus, acts at the mitral cell side of reciprocal synapses by blocking N-type Ca 2÷ channels thereby reducing the release of glutamate. This modulatory influence of the brainstem eventually leads to a disinhibition of mitral cells (Trombley & Shepherd, 1992; Trombley, 1992). This might enhance the OB responses to odorants and/or influence olfactory learning. Another interesting question of olfactory signal processing is the representation of odor m i x t u r e s at the level of the olfactory bulb or the olfactory lobe, the analogon of the olfactory bulb in insects. This problem has recently been studied in the olfactory lobe of the honey bee (Fig. 6) (Joerges et al., 1997; Malaka et al., 1995). The design of 'bioelectronic noses' will require devices that can process, analyze, and classify the complex sensory signals in such a way that accurate identification of odors over a wide range of concentrations and against noisy backgrounds will be possible. Therefore the internal representations of
Bioelectronic noses: a status report Part 1
odors have to be investigated. Optically recorded spatial activity patterns evoked by different odors and mixtures are odor specific and distributed. The responses to natural plant extracts (which are complex blends with dozens to hundreds of components) are not fundamentally different from those of pure substances. Fig. 7 shows as one example the activity patterns that are evoked by the stimuli citral alone or hexanol alone. The pattern produced by the mixture of these odorants is - on the first approximation - a combination of both single component patterns. But comparing it to the arithmetic sum of the two single patterns shows that some differences exist: One glomerulus is activated less than by citral alone (marked with triangle), indicating an inhibitory interaction between hexanol and citral for this site. Another site is activated stronger than predicted by the sum (marked with star), indicating synergistic mixture effects. Thus, the mixture evokes a pattern that is a nonlinear combination of the single component patterns. These results indicate that nonlinear network interactions (mainly through inhibitory interneurons) help the brain to form unique internal representations for complex natural odor blends. Unfortunately, relatively little is known about the central processing of olfactory stimuli. The neurons of the projection areas of the olfactory tract in the CNS have been studied very little with electrophysiological or biochemical techniques, so that there is presently no coherent view of their function. The precise relationships between higher olfactory signal processing and behavior are therefore currently not understood. Little is also known about other cortical regions that might be involved in the processing of olfactory information. Results obtained by positron emission tomography (PET) and functional magnetic resonance imaging (fMRI) show that in addition to the bilateral increase of cerebral blood flow in the piriform cortex, the insular cortex and the right orbitofrontal cortex are also activated by odorous stimulation (Zatorre et al., 1992). In magnetoencephalographic studies brain areas can be identified that generate olfactory bioresponses in humans (Kettenmann et al., subm.). Bilateral activation was observed in the temporal lobes and parts of the insular cortex at different latencies during the first second after olfactory stimulation by vanillin and hydrogen sulfide. Apart from the known primary olfactory areas these 489
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Fig. 6. Olfactoo' senso~ system o f insect." sensoo, cells are located in the antennae projecting into distinct glomeruli of the antennal lobe. Distinct odors elicit responses in specific regions of the lobe. For details of the latter, see Fig. 7.
A
B
Citral
C
Hexanol
D
Mixture
Fig. 7. (A) Antennal lobe o f the honeybee (computer reconstruction from 50 confocal thin sections of an antennal lobe preparation) (B) and (C) Spatial activity patterns for citral and hexanol in one animal. View of the antennal lobe (250 txrn x 250 txrn). Dark color: strong activity; white: no activity. (D) Activity pattern evoked by the mixture of citral and hexanol. For details, see text.
secondary areas could be differentiated with respect to the hedonic properties of the odorants.
UNLINKED REFERENCES G6pel, in press Kettenmann et al., submitted 490
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APPENDIX Presentations at the W o r k s h o p "Bioelectronic
Noses
Odor and Molecular Recognition",
Berlin, 18. and 19.10.1996
Biosensors & Bioelectronics
Organizer: Dr. A. Hache (Projekttrager Biologie, Energie, Okologie des BMBF, Berlin
INTRODUCTION Biological Aspects of odor reception (J. Boeckh, University of Regensburg, D) Bioelectronic Aspects of molecular recognition (W. Gt~pel, University of Ttibingen, D)
ODOR SENSATION AND MOLECULAR RECOGNITION IN ANIMALS Complex signal processing of olfactory signals: the example of cortical representation by means of imaging processing (G. Kobal, University of Erlangen, D) Lectines and their influence on olfactory reception of vertebrates (R. Apfelbach, University of Ttibingen, D) Functional reconstitution of olfactory systems (H. Hatt, University of Bochum, D) Olfactory coding in the nerve systems of insects (J. Joerges, R. Malaka, Universities of Karlsruhe and Berlin, D
Bioelectronic noses: a status report Part 1
CELLS AND CELL ARRAYS IN VITRO FOR DETECTING ODORS AND FOR MOLECULAR RECOGNITION Electronic signal recording from neuronal tissues: Retina as a case study (H. H~immerle, Natural and Medical Sciences Institute, Reutlingen, D) Molecular recognition with neuronal networks in vitro: extracellular recordings of network signals (Ch. Ziegler, University of Ttibingen, D) Cells on sensors: cellular aspects of neuronal recognition (L. Laxhuber, CellControl Biomedical Laboratories Mtinchen, D)
BIOMIMETIC STRUCTURES FOR ODOR DETECTION AND MOLECULAR RECOGNITION Synthetic receptors based on combinatorial cyclopeptide libraries (G. Jung, University of TUbingen) Synthesis and fine-tuning of macrocyclic oligo-amides and sulfonamides as biomimetic receptor molecules for odor sensors (F. V6gtle, University of Bonn, D)
NEURONAL PROCESSING OF OLFACTORY SIGNALS Data and hypothesis for coding odors at different levels of neuronal organization (J. Boeckh, University of Regensburg, D) Neuronal representation of water soluble odorants in fish (S. Korsching, University of K61n, D) Lectin binding properties of olfactory subsystems of vertebrates (D. L. Meyer, University of GOttingen, D)
BIOMOLECULAR ASPECTS: RECEPTORS; BINDING PROTEINS, AND SIGNAL TRANSDUCTION Receptors and transduction mechanisms of olfactory cells (H. Breer, University of Hohenstein, D) Transduction mechanisms in olfactory cells of frog: Approaches to design bioelectronic sensors (D. Schild, University of G6ttingen, D) Signal generation in visual and odor cells - differences and similarities (U. B. Kaupp, Research Center Jialich (KFA), D)
BIOMIMETIC AND MOLECULAR PATTERN RECOGNITION Molecular, biological and biomimetic systems for signal recognition and signal amplification (H. L. Schmidt, University of WeihenstephanMtinchen, D) Biomimetic, supramolecular, and molecular structures for sensor arrays for molecular pattern recognition (W. G6pel, University of TUbingen, D)
BIOINFORMATIC ASPECTS OF ODOR RECOGNITION Molecular pattern recognition (A. Zell, University of Ttibingen, D) Efficient methods for analyzing high dimensional data (V. Heun, University of Mtinchen, D)
493