- Email: [email protected]
Sensory Biology: Structure of an Insect Chemoreceptor
Current Biology
Dispatches inhibition during action preparation, such as to prevent impulsive responses, to delay the execution of motor plans until the right moment, or to inhibit competing or undesirable behavioral options [15,16]. Posterior parietal cortex, and in particular the negative motor area described by Desmurget et al. [1], may be well suited to mediate such effects [17]. Additional research is needed to critically investigate these ideas and to link them to neuropsychiatric phenomena [18]. For instance, given the aforesaid, it may not be surprising that parietal lesions can cause involuntary limb movements. This is the case in the posterior variant of the alien hand syndrome [19], which well might reflect patients’ inability to inhibit action opportunities [20]. Clearly, the study of Desmurget et al. [1] provides ‘stimulating’ clues that will fuel future investigations about how posterior parietal cortex could support us in realizing an optimal course of action through both the excitation and inhibition of goal-directed movement.
REFERENCES 1. Desmurget, M., Richard, N., Beuriat, P.-A., Szathmari, A., Mottolese, C., Duhamel, J.-R., and Sirigu, A. (2018). Selective inhibition of volitional hand movements after stimulation of the dorsoposterior parietal cortex in humans. Curr. Biol. 28, 3303–3309.
2. Borchers, S., Himmelbach, M., Logothetis, N., and Karnath, H.O. (2011). Direct electrical stimulation of human cortex - the gold standard for mapping brain functions? Nat. Rev. Neurosci. 13, 63–70. 3. Desmurget, M., and Sirigu, A. (2015). Revealing humans’ sensorimotor functions with electrical cortical stimulation. Philos. Trans. R. Soc. Lond. B 370, 20140207. 4. Penfield, W., and Boldrey, E. (1937). Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain 60, 389–443. 5. Lu¨ders, H.O., Dinner, D.S., Morris, H.H., Wyllie, E., and Comair, Y.G. (1995). Cortical electrical stimulation in humans. The negative motor areas. Adv. Neurol. 67, 115–129. 6. Filevich, E., Ku¨hn, S., and Haggard, P. (2012). Negative motor phenomena in cortical stimulation: implications for inhibitory control of human action. Cortex 48, 1251–1261. 7. Aron, A.R., Robbins, T.W., and Poldrack, R.A. (2014). Inhibition and the right inferior frontal cortex: one decade on. Trends Cogn. Sci. 18, 177–185. 8. Andersen, R.A., and Cui, H. (2009). Intention, action planning, and decision making in parietal-frontal circuits. Neuron 63, 568–583. 9. Culham, J.C., Cavina-Pratesi, C., and Singhal, A. (2006). The role of parietal cortex in visuomotor control: what have we learned from neuroimaging? Neuropsychologia 44, 2668–2684. 10. Lindner, A., Iyer, A., Kagan, I., and Andersen, R.A. (2010). Human posterior parietal cortex plans where to reach and what to avoid. J. Neurosci. 30, 11715–11725.
11. Klaes, C., Westendorff, S., Chakrabarti, S., and Gail, A. (2011). Choosing goals, not rules: deciding among rule-based action plans. Neuron 70, 536–548. 12. Iyer, A., Lindner, A., Kagan, I., and Andersen, R.A. (2010). Motor preparatory activity in posterior parietal cortex is modulated by subjective absolute value. PLoS Biol. 8, e1000444. 13. Cisek, P. (2012). Making decisions through a distributed consensus. Curr. Opin. Neurobiol. 22, 927–936. 14. Mostofsky, S.H., and Simmonds, D.J. (2008). Response inhibition and response selection: two sides of the same coin. J. Cogn. Neurosci. 20, 751–761. 15. Duque, J., Greenhouse, I., Labruna, L., and Ivry, R.B. (2017). Physiological markers of motor inhibition during human behavior. Trends Neurosci. 40, 219–236. 16. Bestmann, S., and Duque, J. (2016). Transcranial magnetic stimulation: decomposing the processes underlying action preparation. Neuroscientist 22, 392–405. 17. Rathelot, J.A., Dum, R.P., and Strick, P.L. (2017). Posterior parietal cortex contains a command apparatus for hand movements. Proc. Natl. Acad. Sci. USA 114, 4255–4260. 18. Aron, A.R. (2011). From reactive to proactive and selective control: developing a richer model for stopping inappropriate responses. Biol. Psychiatry. 69, e55–e68. 19. Hassan, A., and Josephs, K.A. (2016). Alien hand syndrome. Curr. Neurol. Neurosci. Rep. 16, 73. 20. McBride, J., Sumner, P., Jackson, S.R., Bajaj, N., and Husain, M. (2013). Exaggerated object affordance and absent automatic inhibition in alien hand syndrome. Cortex 49, 2040–2054.
Sensory Biology: Structure of an Insect Chemoreceptor Yichen Luo and John R. Carlson* Dept. of Molecular, Cellular and Developmental Biology, Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06520-8103, USA *Correspondence: [email protected] https://doi.org/10.1016/j.cub.2018.09.002
Odorant receptors detect a vast diversity of chemical compounds and underlie many aspects of life. The structure of insect odorant receptors, however, has remained unknown. A cryo-EM study now reveals an intriguing architecture. Twenty years have elapsed since the first insect odorant receptors were identified [1,2]. Odorant receptors may be the
largest family of ion channels in the animal kingdom: an enormous number of insect species have them, each species has
R1202 Current Biology 28, R1190–R1211, October 22, 2018 ª 2018 Elsevier Ltd.
many of them, and their sequences are highly divergent. The odorant receptors detect and discriminate among
Current Biology
Dispatches A
Pocket
B
C
Top view
Lateral view Extracelluar
Intracellular
Anchor domains
Lateral conduits Current Biology
Figure 1. The structure of the Orco tetramer. (A) Top view of the Orco tetramer from the extracellular side, indicating the approximate position of a potential ligand-binding pocket (yellow circle) in one of the four subunits. All images of the model were created using PyMOL (PyMOL Molecular Graphics System, Version 2.0, Schrodinger, LLC), based on the Orco structure deposited in the Protein Data Bank under accession number 6C70. (B) Lateral view of the Orco tetramer, showing anchor domains that mediate subunit–subunit interactions. (C) Proposed ion permeation pathways, viewed from the side (left) or the top (right). Ions are proposed to pass vertically through the membrane (solid line in lateral view). It is possible that a structural rearrangement occurs and allows ions to continue to pass vertically through the anchor domain (dotted line). Alternatively, ions may pass through any of four lateral conduits (dashed lines in lateral and top views). Adapted from [4].
innumerable chemical cues in an insect’s environment. We have learned much about odorant receptor expression and function, and how the signals they produce are transformed through several layers of neural circuitry to drive olfactory behavior [3]. Yet, their molecular structure has been unknown —until a new study by Joel Butterwick and colleagues [4]. Insect odor receptors were originally presumed to be G protein coupled receptors (GPCRs), by analogy to those of mammals and nematodes, and when isolated, they contained seven transmembrane domains, like GPCRs. However, the sequences of odorant receptors showed no similarity whatsoever to those of GPCRs. Moreover, odorant receptors were then found to have a topology — with the amino terminus facing inside the cell and the carboxyl terminus outside (Nin–Cout)— that is opposite to that of GPCRs [5,6], raising eyebrows in the field. Next, physiological studies revealed that odorant receptors could function as odorant-gated ion channels [7,8]. This succession of findings piqued increasing curiosity about their structure. Many studies have sought to illuminate the structure of odorant receptors by evolutionary analysis of their primary sequences, or by mutational analysis [9]. What has been severely needed, however, was a direct determination of their molecular structure — a daunting challenge. Butterwick and colleagues [4]
have now used cryo-EM to supply the first structure, at 3.5 A˚ resolution, a landmark accomplishment in the field. The structure that has been solved is actually that of a tetramer of a co-receptor called Orco (Odorant receptor co-receptor) [5,10,11]. Orco is closely related to odorant receptors and was in fact for many years called Or83b. However, Orco is distinct from canonical odorant receptors in several ways. Most olfactory receptor neurons (ORNs) coexpress one member of the odorant receptor family together with Orco. Orco is essential for membrane trafficking and function of odorant receptors. Whereas canonical odorant receptors are highly divergent in sequence both within and across species, Orco is relatively conserved across insect orders [12]. Butterwick et al. screened Orco orthologs from various insects and identified one from the parasitic fig wasp Apocrypta bakeri by virtue of its ability to form stable higher-order complexes. This Orco acted as a functional cation channel in HEK293 cells. Monoclonal antibodies were raised against it and the antigenbinding fragments (Fabs) were used to aid in structural analysis. Cryo-EM analysis revealed an intriguing tetrameric structure. From the outside of the cell, the Orco tetramer looks like a pinwheel, arranged around a central pore (Figure 1A). Small intracellular domains extend into the cytoplasm and are called anchor domains; these account for
most of the inter-subunit interactions (Figure 1B). Each of the four subunits has seven helical transmembrane segments, with an overall Nin–Cout topology, confirming earlier studies [5,6]. Of the seven transmembrane segments (S1–S7), S7 is nearest to the central four-fold axis and contributes most if not all of the residues of the pore. S1–S6 spread out to create a pocket in the extracellular surface that is 10 A˚ deep and 20 A˚ across — a likely site for ligands that gate the channel (Figure 1A). The channel pore is most narrow near the extracellular side (Figure 1C), where it is constricted by two hydrophobic and highly conserved amino acids (Leu473 and Val469). The diameter of the channel at this position is only 2 A˚, which is too narrow for hydrated ions to flow through, indicating that the structure is likely to represent the closed state of the channel. It is possible that in the open state, ions may pass through a continuous channel along the central axis of the tetramer into the cytoplasm, but the structure also reveals an intriguing alternative possibility. The external pore diverges into four lateral conduits at the junctions of the subunits through which ions could pass (Figure 1C). Thus, ions could enter through a single pore at the extracellular surface and then move through any of four symmetric passageways into the cytoplasm — a curious and somehow aesthetically appealing architecture.
Current Biology 28, R1190–R1211, October 22, 2018 R1203
Current Biology
Dispatches Most of the conserved amino acid residues in Orco either line the pore or reside in the anchor domain, which is likely to mediate subunit interactions. Canonical odorant receptors are highly divergent in sequence, but the distribution of conserved residues resembles that found among Orcos of different species. This resemblance, along with other evidence, supports a model in which the structure of a canonical odorant receptor is similar to that of Orco. Butterwick and colleagues [4] reasonably propose that a native olfactory receptor in an individual olfactory sensor neuron is a tetrameric complex of Orco and a canonical odorant receptor, likely consisting of two molecules of Orco and two of the odorant receptor that the cell expresses. The structure provided by Butterwick and colleagues [4] is a great step forward in the field. After the first insect odorant receptors were identified 20 years ago, it took seven years for an odorant receptor to be drawn in a two-dimensional representation with correct transmembrane topology [5,6]. Now, after another 12 years, the first three-dimensional representation is at last available and many directions for future work can be envisioned. One hopes that the current structure will provide precedent for the direct determination of structures of Orco– odorant receptor complexes. It will be interesting to see them in both open and closed states, bound to various ligands and unbound. Analysis of odorant receptor structure and function may benefit from advanced computational techniques, such as protein–ligand docking software, and from an immense and rapidly growing database that now contains on the order of 10,000 sequenced odorant receptor genes from a great bestiary of diverse insects. Especially interesting is the prospect of correlating structure with odorant response profiles, which have been defined for many odorant receptors, including those of Drosophila melanogaster [13] and the malaria mosquito Anopheles gambiae [14,15]. Many intriguing questions await analysis at the structural level. First, different olfactory sensory neurons have different levels of spontaneous firing, which has implications for their roles in encoding olfactory information. The spontaneous
firing rate is conferred by the odorant receptor that the neuron expresses [16]. What, then, characterizes the structure of odorant receptors that confer high spontaneous firing rates? Some odorant receptors are narrowly tuned, responding strongly to only one tested odorant, whereas others are broadly tuned, responding strongly to many [13]. Or56a of Drosophila, for example, is exquisitely tuned to geosmin, which is produced by certain microbes and is lethal to flies [17]. Does geosmin fit snugly into the pocket created by the splaying out of S1–S6 at the extracellular face of Or56a? Some odorant receptors show both excitatory and inhibitory responses [16]. For example, an olfactory sensory neuron expressing Or59b increases its firing rate upon stimulation with ethyl acetate but decreases firing when exposed to linalool. Butterwick and colleagues [4] suggest that odorant receptors may contain multiple binding sites. Do ethyl acetate and linalool bind to different sites in Or59b, or do they bind to the same site but trigger different conformational changes? Different odorants activate receptors with different dynamics [18]. The dynamics depend on both the odorant and the receptor. For example, two odorants may elicit comparable initial firing frequencies from an olfactory sensory neuron expressing an odorant receptor, but the response to one odorant terminates abruptly while the response to the other is dramatically ‘supersustained’. How do the two odorants interact with the receptor? Odorant receptors and Orco form a lineage within an insect chemoreceptor gene superfamily that includes Gustatory receptor genes. Gustatory receptors are expressed in taste neurons, where many respond to tastants [19]. Less is known about the topology and signaling of Gustatory receptors than odorant receptors, but the new structure of Orco may provide precedent for the eventual determination of a Gr structure. Structural analysis of insect chemoreceptors may in the long term lead to practical benefits for humankind. For example, insect vectors of disease use odorant receptors to detect their human hosts [20]. Knowing the structure of the receptors that mediate this process may aid in the rational design of compounds that interfere with their signaling and reduce the transmission of disease. In summary, the structure
R1204 Current Biology 28, R1190–R1211, October 22, 2018
provided by Butterwick and colleagues [4] brings a large and fascinating family of receptors into sharp focus. It also provides an excellent point of departure for many journeys ahead. REFERENCES 1. Clyne, P.J., Warr, C.G., Freeman, M.R., Lessing, D., Kim, J., and Carlson, J.R. (1999). A novel family of divergent seventransmembrane proteins: candidate odorant receptors in Drosophila. Neuron 22, 327–338. 2. Vosshall, L.B., Amrein, H., Morozov, P.S., Rzhetsky, A., and Axel, R. (1999). A spatial map of olfactory receptor expression in the Drosophila antenna. Cell 96, 725–736. 3. Wilson, R.I. (2013). Early olfactory processing in Drosophila: mechanisms and principles. Annu. Rev. Neurosci. 36, 217–241. 4. Butterwick, J.A., Del Marmol, J., Kim, K.H., Kahlson, M.A., Rogow, J.A., Walz, T., and Ruta, V. (2018). Cryo-EM structure of the insect olfactory receptor Orco. Nature 560, 447–452. 5. Benton, R., Sachse, S., Michnick, S.W., and Vosshall, L.B. (2006). Atypical membrane topology and heteromeric function of Drosophila odorant receptors in vivo. PLoS Biol. 4, e20. 6. Smart, R., Kiely, A., Beale, M., Vargas, E., Carraher, C., Kralicek, A.V., Christie, D.L., Chen, C., Newcomb, R.D., and Warr, C.G. (2008). Drosophila odorant receptors are novel seven transmembrane domain proteins that can signal independently of heterotrimeric G proteins. Insect. Biochem. Mol. Biol. 38, 770–780. 7. Wicher, D., Schafer, R., Bauernfeind, R., Stensmyr, M.C., Heller, R., Heinemann, S.H., and Hansson, B.S. (2008). Drosophila odorant receptors are both ligand-gated and cyclicnucleotide-activated cation channels. Nature 452, 1007–1011. 8. Sato, K., Pellegrino, M., Nakagawa, T., Nakagawa, T., Vosshall, L.B., and Touhara, K. (2008). Insect olfactory receptors are heteromeric ligand-gated ion channels. Nature 452, 1002–1006. 9. Hughes, D.T., Wang, G., Zwiebel, L.J., and Luetje, C.W. (2014). A determinant of odorant specificity is located at the extracellular loop 2-transmembrane domain 4 interface of an Anopheles gambiae odorant receptor subunit. Chem. Senses 39, 761–769. 10. Vosshall, L.B., Wong, A.M., and Axel, R. (2000). An olfactory sensory map in the fly brain. Cell 102, 147–159. 11. Larsson, M.C., Domingos, A.I., Jones, W.D., Chiappe, M.E., Amrein, H., and Vosshall, L.B. (2004). Or83b encodes a broadly expressed odorant receptor essential for Drosophila olfaction. Neuron 43, 703–714. 12. Jones, W.D., Nguyen, T.A., Kloss, B., Lee, K.J., and Vosshall, L.B. (2005). Functional conservation of an insect odorant receptor gene across 250 million years of evolution. Curr. Biol. 15, R119–R121.
Current Biology
Dispatches 13. Hallem, E.A., and Carlson, J.R. (2006). Coding of odors by a receptor repertoire. Cell 125, 143–160. 14. Carey, A.F., Wang, G., Su, C.Y., Zwiebel, L.J., and Carlson, J.R. (2010). Odorant reception in the malaria mosquito Anopheles gambiae. Nature 464, 66–71. 15. Wang, G., Carey, A.F., Carlson, J.R., and Zwiebel, L.J. (2010). Molecular basis of odor coding in the malaria vector mosquito
Anopheles gambiae. Proc. Natl. Acad. Sci. USA 107, 4418–4423. 16. Hallem, E.A., Ho, M.G., and Carlson, J.R. (2004). The molecular basis of odor coding in the Drosophila antenna. Cell 117, 965–979. 17. Stensmyr, M.C., Dweck, H.K., Farhan, A., Ibba, I., Strutz, A., Mukunda, L., Linz, J., Grabe, V., Steck, K., Lavista-Llanos, S., et al. (2012). A conserved dedicated olfactory circuit for detecting harmful microbes in Drosophila. Cell 151, 1345–1357.
18. Montague, S.A., Mathew, D., and Carlson, J.R. (2011). Similar odorants elicit different behavioral and physiological responses, some supersustained. J. Neurosci. 31, 7891–7899. 19. Liman, E.R., Zhang, Y.V., and Montell, C. (2014). Peripheral coding of taste. Neuron 81, 984–1000. 20. McBride, C.S. (2016). Genes and odors underlying the recent evolution of mosquito preference for humans. Curr. Biol. 26, R41–R46.
Drug Addiction: Mechanisms of Nicotine Dependence Unmasked by Gene Editing William M. Howe and Paul J. Kenny* Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029-6574, USA *Correspondence: [email protected] https://doi.org/10.1016/j.cub.2018.09.003
New gene editing technologies are enabling exploration of previously intractable features of genetic risk for drug addiction. A recent study using this technology reveals new insights into how a mutation linked to tobacco dependence influences the addictive properties of nicotine. Cigarette smoking is one the leading preventable causes of diseases worldwide [1,2]. The development and persistence of cigarette smoking is believed to stem from the actions of nicotine [3], which can potently modulate brain activity by acting at neuronal nicotinic acetylcholine receptors (nAChRs). These nAChRs are distributed throughout the brain, including neural circuits known to control the rewarding properties of nicotine and other drugs of abuse [4]. Just over 10 years ago, a single nucleotide polymorphism (SNP) in the CHRNA5 gene (rs16969968), which encodes the a5 nAChR subunit (termed a5* nAChRs), was identified as a major risk factor for nicotine dependence [5,6], and many of the health problems associated with the tobacco habit [7]; a surprising result given the small fraction of the total number of nAChRs in the brain that contain the a5 subunit. The a5* rs16969968 SNP is thought to reduce the function of the nAChRs that incorporate the mutant subunit [8,9]. Studies investigating how this loss of function may influence brain responses to
nicotine have given key insights into the mechanisms of nicotine dependence. Specifically, transgenic mice engineered to completely lack expression of a5 nAChR subunits (Chrna5–/– mice) are less sensitive to aversive qualities of nicotine that normally limit intake [10]. This ‘brake’ on nicotine consumption is relayed by neural connections between the medial habenula and the interpeduncular nucleus, which are enriched in a5* nAChRs. Heavy smoking in carriers of the rs16969968 SNP may therefore reflect diminished capacity of a5* nAChRs to stimulate the medial habenulainterpeduncular nucleus pathway and thereby curb nicotine consumption [10,11]. An important caveat to these previous findings is that the Chrna5–/– mice used in these studies completely lack a5 nAChRs, which contrasts with humans who carry the rs16969968 (or other) SNP and express a5* nAChRs with altered function. Hence, it is possible that complete genetic ablation of a5 subunits in Chrna5–/– mice has different outcomes than mutations that more subtly alter a5* nAChRs function. Consequently, animal
models that more faithfully capture the influence of the rs16969968 risk allele in the brains of smokers are needed. As they report in this issue of Current Biology, Forget et al. [12] capitalized on precision gene editing technologies to generate a transgenic rat that expresses the rs16969968 SNP in the Chrna5 gene and show that this manipulation markedly alters addiction-relevant actions of nicotine in the mutant animals (Figure 1). First, Forget et al. [12] used zincfinger nucleases to introduce the rs16969968 SNP into the Chrna5 gene of rats. Using this gene editing approach, they observed little evidence of ‘off-target’ genetic effects, suggesting that the modification was efficacious and accurate. For comparison, they used the same approach to completely ablate the Chrna5 gene in rats, similar to the Chrna5–/– mice described above. As expected, a5 subunits were undetectable in the brains of the rats in which the Chrna5 gene was entirely ablated, although the total amounts of nAChRs detected across multiple brain
Current Biology 28, R1190–R1211, October 22, 2018 ª 2018 Elsevier Ltd. R1205
Dispatches inhibition during action preparation, such as to prevent impulsive responses, to delay the execution of motor plans until the right moment, or to inhibit competing or undesirable behavioral options [15,16]. Posterior parietal cortex, and in particular the negative motor area described by Desmurget et al. [1], may be well suited to mediate such effects [17]. Additional research is needed to critically investigate these ideas and to link them to neuropsychiatric phenomena [18]. For instance, given the aforesaid, it may not be surprising that parietal lesions can cause involuntary limb movements. This is the case in the posterior variant of the alien hand syndrome [19], which well might reflect patients’ inability to inhibit action opportunities [20]. Clearly, the study of Desmurget et al. [1] provides ‘stimulating’ clues that will fuel future investigations about how posterior parietal cortex could support us in realizing an optimal course of action through both the excitation and inhibition of goal-directed movement.
REFERENCES 1. Desmurget, M., Richard, N., Beuriat, P.-A., Szathmari, A., Mottolese, C., Duhamel, J.-R., and Sirigu, A. (2018). Selective inhibition of volitional hand movements after stimulation of the dorsoposterior parietal cortex in humans. Curr. Biol. 28, 3303–3309.
2. Borchers, S., Himmelbach, M., Logothetis, N., and Karnath, H.O. (2011). Direct electrical stimulation of human cortex - the gold standard for mapping brain functions? Nat. Rev. Neurosci. 13, 63–70. 3. Desmurget, M., and Sirigu, A. (2015). Revealing humans’ sensorimotor functions with electrical cortical stimulation. Philos. Trans. R. Soc. Lond. B 370, 20140207. 4. Penfield, W., and Boldrey, E. (1937). Somatic motor and sensory representation in the cerebral cortex of man as studied by electrical stimulation. Brain 60, 389–443. 5. Lu¨ders, H.O., Dinner, D.S., Morris, H.H., Wyllie, E., and Comair, Y.G. (1995). Cortical electrical stimulation in humans. The negative motor areas. Adv. Neurol. 67, 115–129. 6. Filevich, E., Ku¨hn, S., and Haggard, P. (2012). Negative motor phenomena in cortical stimulation: implications for inhibitory control of human action. Cortex 48, 1251–1261. 7. Aron, A.R., Robbins, T.W., and Poldrack, R.A. (2014). Inhibition and the right inferior frontal cortex: one decade on. Trends Cogn. Sci. 18, 177–185. 8. Andersen, R.A., and Cui, H. (2009). Intention, action planning, and decision making in parietal-frontal circuits. Neuron 63, 568–583. 9. Culham, J.C., Cavina-Pratesi, C., and Singhal, A. (2006). The role of parietal cortex in visuomotor control: what have we learned from neuroimaging? Neuropsychologia 44, 2668–2684. 10. Lindner, A., Iyer, A., Kagan, I., and Andersen, R.A. (2010). Human posterior parietal cortex plans where to reach and what to avoid. J. Neurosci. 30, 11715–11725.
11. Klaes, C., Westendorff, S., Chakrabarti, S., and Gail, A. (2011). Choosing goals, not rules: deciding among rule-based action plans. Neuron 70, 536–548. 12. Iyer, A., Lindner, A., Kagan, I., and Andersen, R.A. (2010). Motor preparatory activity in posterior parietal cortex is modulated by subjective absolute value. PLoS Biol. 8, e1000444. 13. Cisek, P. (2012). Making decisions through a distributed consensus. Curr. Opin. Neurobiol. 22, 927–936. 14. Mostofsky, S.H., and Simmonds, D.J. (2008). Response inhibition and response selection: two sides of the same coin. J. Cogn. Neurosci. 20, 751–761. 15. Duque, J., Greenhouse, I., Labruna, L., and Ivry, R.B. (2017). Physiological markers of motor inhibition during human behavior. Trends Neurosci. 40, 219–236. 16. Bestmann, S., and Duque, J. (2016). Transcranial magnetic stimulation: decomposing the processes underlying action preparation. Neuroscientist 22, 392–405. 17. Rathelot, J.A., Dum, R.P., and Strick, P.L. (2017). Posterior parietal cortex contains a command apparatus for hand movements. Proc. Natl. Acad. Sci. USA 114, 4255–4260. 18. Aron, A.R. (2011). From reactive to proactive and selective control: developing a richer model for stopping inappropriate responses. Biol. Psychiatry. 69, e55–e68. 19. Hassan, A., and Josephs, K.A. (2016). Alien hand syndrome. Curr. Neurol. Neurosci. Rep. 16, 73. 20. McBride, J., Sumner, P., Jackson, S.R., Bajaj, N., and Husain, M. (2013). Exaggerated object affordance and absent automatic inhibition in alien hand syndrome. Cortex 49, 2040–2054.
Sensory Biology: Structure of an Insect Chemoreceptor Yichen Luo and John R. Carlson* Dept. of Molecular, Cellular and Developmental Biology, Interdepartmental Neuroscience Program, Yale University, New Haven, CT 06520-8103, USA *Correspondence: [email protected] https://doi.org/10.1016/j.cub.2018.09.002
Odorant receptors detect a vast diversity of chemical compounds and underlie many aspects of life. The structure of insect odorant receptors, however, has remained unknown. A cryo-EM study now reveals an intriguing architecture. Twenty years have elapsed since the first insect odorant receptors were identified [1,2]. Odorant receptors may be the
largest family of ion channels in the animal kingdom: an enormous number of insect species have them, each species has
R1202 Current Biology 28, R1190–R1211, October 22, 2018 ª 2018 Elsevier Ltd.
many of them, and their sequences are highly divergent. The odorant receptors detect and discriminate among
Current Biology
Dispatches A
B
C
Top view
Lateral view Extracelluar
Intracellular
Anchor domains
Lateral conduits Current Biology
Figure 1. The structure of the Orco tetramer. (A) Top view of the Orco tetramer from the extracellular side, indicating the approximate position of a potential ligand-binding pocket (yellow circle) in one of the four subunits. All images of the model were created using PyMOL (PyMOL Molecular Graphics System, Version 2.0, Schrodinger, LLC), based on the Orco structure deposited in the Protein Data Bank under accession number 6C70. (B) Lateral view of the Orco tetramer, showing anchor domains that mediate subunit–subunit interactions. (C) Proposed ion permeation pathways, viewed from the side (left) or the top (right). Ions are proposed to pass vertically through the membrane (solid line in lateral view). It is possible that a structural rearrangement occurs and allows ions to continue to pass vertically through the anchor domain (dotted line). Alternatively, ions may pass through any of four lateral conduits (dashed lines in lateral and top views). Adapted from [4].
innumerable chemical cues in an insect’s environment. We have learned much about odorant receptor expression and function, and how the signals they produce are transformed through several layers of neural circuitry to drive olfactory behavior [3]. Yet, their molecular structure has been unknown —until a new study by Joel Butterwick and colleagues [4]. Insect odor receptors were originally presumed to be G protein coupled receptors (GPCRs), by analogy to those of mammals and nematodes, and when isolated, they contained seven transmembrane domains, like GPCRs. However, the sequences of odorant receptors showed no similarity whatsoever to those of GPCRs. Moreover, odorant receptors were then found to have a topology — with the amino terminus facing inside the cell and the carboxyl terminus outside (Nin–Cout)— that is opposite to that of GPCRs [5,6], raising eyebrows in the field. Next, physiological studies revealed that odorant receptors could function as odorant-gated ion channels [7,8]. This succession of findings piqued increasing curiosity about their structure. Many studies have sought to illuminate the structure of odorant receptors by evolutionary analysis of their primary sequences, or by mutational analysis [9]. What has been severely needed, however, was a direct determination of their molecular structure — a daunting challenge. Butterwick and colleagues [4]
have now used cryo-EM to supply the first structure, at 3.5 A˚ resolution, a landmark accomplishment in the field. The structure that has been solved is actually that of a tetramer of a co-receptor called Orco (Odorant receptor co-receptor) [5,10,11]. Orco is closely related to odorant receptors and was in fact for many years called Or83b. However, Orco is distinct from canonical odorant receptors in several ways. Most olfactory receptor neurons (ORNs) coexpress one member of the odorant receptor family together with Orco. Orco is essential for membrane trafficking and function of odorant receptors. Whereas canonical odorant receptors are highly divergent in sequence both within and across species, Orco is relatively conserved across insect orders [12]. Butterwick et al. screened Orco orthologs from various insects and identified one from the parasitic fig wasp Apocrypta bakeri by virtue of its ability to form stable higher-order complexes. This Orco acted as a functional cation channel in HEK293 cells. Monoclonal antibodies were raised against it and the antigenbinding fragments (Fabs) were used to aid in structural analysis. Cryo-EM analysis revealed an intriguing tetrameric structure. From the outside of the cell, the Orco tetramer looks like a pinwheel, arranged around a central pore (Figure 1A). Small intracellular domains extend into the cytoplasm and are called anchor domains; these account for
most of the inter-subunit interactions (Figure 1B). Each of the four subunits has seven helical transmembrane segments, with an overall Nin–Cout topology, confirming earlier studies [5,6]. Of the seven transmembrane segments (S1–S7), S7 is nearest to the central four-fold axis and contributes most if not all of the residues of the pore. S1–S6 spread out to create a pocket in the extracellular surface that is 10 A˚ deep and 20 A˚ across — a likely site for ligands that gate the channel (Figure 1A). The channel pore is most narrow near the extracellular side (Figure 1C), where it is constricted by two hydrophobic and highly conserved amino acids (Leu473 and Val469). The diameter of the channel at this position is only 2 A˚, which is too narrow for hydrated ions to flow through, indicating that the structure is likely to represent the closed state of the channel. It is possible that in the open state, ions may pass through a continuous channel along the central axis of the tetramer into the cytoplasm, but the structure also reveals an intriguing alternative possibility. The external pore diverges into four lateral conduits at the junctions of the subunits through which ions could pass (Figure 1C). Thus, ions could enter through a single pore at the extracellular surface and then move through any of four symmetric passageways into the cytoplasm — a curious and somehow aesthetically appealing architecture.
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Dispatches Most of the conserved amino acid residues in Orco either line the pore or reside in the anchor domain, which is likely to mediate subunit interactions. Canonical odorant receptors are highly divergent in sequence, but the distribution of conserved residues resembles that found among Orcos of different species. This resemblance, along with other evidence, supports a model in which the structure of a canonical odorant receptor is similar to that of Orco. Butterwick and colleagues [4] reasonably propose that a native olfactory receptor in an individual olfactory sensor neuron is a tetrameric complex of Orco and a canonical odorant receptor, likely consisting of two molecules of Orco and two of the odorant receptor that the cell expresses. The structure provided by Butterwick and colleagues [4] is a great step forward in the field. After the first insect odorant receptors were identified 20 years ago, it took seven years for an odorant receptor to be drawn in a two-dimensional representation with correct transmembrane topology [5,6]. Now, after another 12 years, the first three-dimensional representation is at last available and many directions for future work can be envisioned. One hopes that the current structure will provide precedent for the direct determination of structures of Orco– odorant receptor complexes. It will be interesting to see them in both open and closed states, bound to various ligands and unbound. Analysis of odorant receptor structure and function may benefit from advanced computational techniques, such as protein–ligand docking software, and from an immense and rapidly growing database that now contains on the order of 10,000 sequenced odorant receptor genes from a great bestiary of diverse insects. Especially interesting is the prospect of correlating structure with odorant response profiles, which have been defined for many odorant receptors, including those of Drosophila melanogaster [13] and the malaria mosquito Anopheles gambiae [14,15]. Many intriguing questions await analysis at the structural level. First, different olfactory sensory neurons have different levels of spontaneous firing, which has implications for their roles in encoding olfactory information. The spontaneous
firing rate is conferred by the odorant receptor that the neuron expresses [16]. What, then, characterizes the structure of odorant receptors that confer high spontaneous firing rates? Some odorant receptors are narrowly tuned, responding strongly to only one tested odorant, whereas others are broadly tuned, responding strongly to many [13]. Or56a of Drosophila, for example, is exquisitely tuned to geosmin, which is produced by certain microbes and is lethal to flies [17]. Does geosmin fit snugly into the pocket created by the splaying out of S1–S6 at the extracellular face of Or56a? Some odorant receptors show both excitatory and inhibitory responses [16]. For example, an olfactory sensory neuron expressing Or59b increases its firing rate upon stimulation with ethyl acetate but decreases firing when exposed to linalool. Butterwick and colleagues [4] suggest that odorant receptors may contain multiple binding sites. Do ethyl acetate and linalool bind to different sites in Or59b, or do they bind to the same site but trigger different conformational changes? Different odorants activate receptors with different dynamics [18]. The dynamics depend on both the odorant and the receptor. For example, two odorants may elicit comparable initial firing frequencies from an olfactory sensory neuron expressing an odorant receptor, but the response to one odorant terminates abruptly while the response to the other is dramatically ‘supersustained’. How do the two odorants interact with the receptor? Odorant receptors and Orco form a lineage within an insect chemoreceptor gene superfamily that includes Gustatory receptor genes. Gustatory receptors are expressed in taste neurons, where many respond to tastants [19]. Less is known about the topology and signaling of Gustatory receptors than odorant receptors, but the new structure of Orco may provide precedent for the eventual determination of a Gr structure. Structural analysis of insect chemoreceptors may in the long term lead to practical benefits for humankind. For example, insect vectors of disease use odorant receptors to detect their human hosts [20]. Knowing the structure of the receptors that mediate this process may aid in the rational design of compounds that interfere with their signaling and reduce the transmission of disease. In summary, the structure
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provided by Butterwick and colleagues [4] brings a large and fascinating family of receptors into sharp focus. It also provides an excellent point of departure for many journeys ahead. REFERENCES 1. Clyne, P.J., Warr, C.G., Freeman, M.R., Lessing, D., Kim, J., and Carlson, J.R. (1999). A novel family of divergent seventransmembrane proteins: candidate odorant receptors in Drosophila. Neuron 22, 327–338. 2. Vosshall, L.B., Amrein, H., Morozov, P.S., Rzhetsky, A., and Axel, R. (1999). A spatial map of olfactory receptor expression in the Drosophila antenna. Cell 96, 725–736. 3. Wilson, R.I. (2013). Early olfactory processing in Drosophila: mechanisms and principles. Annu. Rev. Neurosci. 36, 217–241. 4. Butterwick, J.A., Del Marmol, J., Kim, K.H., Kahlson, M.A., Rogow, J.A., Walz, T., and Ruta, V. (2018). Cryo-EM structure of the insect olfactory receptor Orco. Nature 560, 447–452. 5. Benton, R., Sachse, S., Michnick, S.W., and Vosshall, L.B. (2006). Atypical membrane topology and heteromeric function of Drosophila odorant receptors in vivo. PLoS Biol. 4, e20. 6. Smart, R., Kiely, A., Beale, M., Vargas, E., Carraher, C., Kralicek, A.V., Christie, D.L., Chen, C., Newcomb, R.D., and Warr, C.G. (2008). Drosophila odorant receptors are novel seven transmembrane domain proteins that can signal independently of heterotrimeric G proteins. Insect. Biochem. Mol. Biol. 38, 770–780. 7. Wicher, D., Schafer, R., Bauernfeind, R., Stensmyr, M.C., Heller, R., Heinemann, S.H., and Hansson, B.S. (2008). Drosophila odorant receptors are both ligand-gated and cyclicnucleotide-activated cation channels. Nature 452, 1007–1011. 8. Sato, K., Pellegrino, M., Nakagawa, T., Nakagawa, T., Vosshall, L.B., and Touhara, K. (2008). Insect olfactory receptors are heteromeric ligand-gated ion channels. Nature 452, 1002–1006. 9. Hughes, D.T., Wang, G., Zwiebel, L.J., and Luetje, C.W. (2014). A determinant of odorant specificity is located at the extracellular loop 2-transmembrane domain 4 interface of an Anopheles gambiae odorant receptor subunit. Chem. Senses 39, 761–769. 10. Vosshall, L.B., Wong, A.M., and Axel, R. (2000). An olfactory sensory map in the fly brain. Cell 102, 147–159. 11. Larsson, M.C., Domingos, A.I., Jones, W.D., Chiappe, M.E., Amrein, H., and Vosshall, L.B. (2004). Or83b encodes a broadly expressed odorant receptor essential for Drosophila olfaction. Neuron 43, 703–714. 12. Jones, W.D., Nguyen, T.A., Kloss, B., Lee, K.J., and Vosshall, L.B. (2005). Functional conservation of an insect odorant receptor gene across 250 million years of evolution. Curr. Biol. 15, R119–R121.
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Dispatches 13. Hallem, E.A., and Carlson, J.R. (2006). Coding of odors by a receptor repertoire. Cell 125, 143–160. 14. Carey, A.F., Wang, G., Su, C.Y., Zwiebel, L.J., and Carlson, J.R. (2010). Odorant reception in the malaria mosquito Anopheles gambiae. Nature 464, 66–71. 15. Wang, G., Carey, A.F., Carlson, J.R., and Zwiebel, L.J. (2010). Molecular basis of odor coding in the malaria vector mosquito
Anopheles gambiae. Proc. Natl. Acad. Sci. USA 107, 4418–4423. 16. Hallem, E.A., Ho, M.G., and Carlson, J.R. (2004). The molecular basis of odor coding in the Drosophila antenna. Cell 117, 965–979. 17. Stensmyr, M.C., Dweck, H.K., Farhan, A., Ibba, I., Strutz, A., Mukunda, L., Linz, J., Grabe, V., Steck, K., Lavista-Llanos, S., et al. (2012). A conserved dedicated olfactory circuit for detecting harmful microbes in Drosophila. Cell 151, 1345–1357.
18. Montague, S.A., Mathew, D., and Carlson, J.R. (2011). Similar odorants elicit different behavioral and physiological responses, some supersustained. J. Neurosci. 31, 7891–7899. 19. Liman, E.R., Zhang, Y.V., and Montell, C. (2014). Peripheral coding of taste. Neuron 81, 984–1000. 20. McBride, C.S. (2016). Genes and odors underlying the recent evolution of mosquito preference for humans. Curr. Biol. 26, R41–R46.
Drug Addiction: Mechanisms of Nicotine Dependence Unmasked by Gene Editing William M. Howe and Paul J. Kenny* Department of Neuroscience, Icahn School of Medicine at Mount Sinai, One Gustave L. Levy Place, New York, NY 10029-6574, USA *Correspondence: [email protected] https://doi.org/10.1016/j.cub.2018.09.003
New gene editing technologies are enabling exploration of previously intractable features of genetic risk for drug addiction. A recent study using this technology reveals new insights into how a mutation linked to tobacco dependence influences the addictive properties of nicotine. Cigarette smoking is one the leading preventable causes of diseases worldwide [1,2]. The development and persistence of cigarette smoking is believed to stem from the actions of nicotine [3], which can potently modulate brain activity by acting at neuronal nicotinic acetylcholine receptors (nAChRs). These nAChRs are distributed throughout the brain, including neural circuits known to control the rewarding properties of nicotine and other drugs of abuse [4]. Just over 10 years ago, a single nucleotide polymorphism (SNP) in the CHRNA5 gene (rs16969968), which encodes the a5 nAChR subunit (termed a5* nAChRs), was identified as a major risk factor for nicotine dependence [5,6], and many of the health problems associated with the tobacco habit [7]; a surprising result given the small fraction of the total number of nAChRs in the brain that contain the a5 subunit. The a5* rs16969968 SNP is thought to reduce the function of the nAChRs that incorporate the mutant subunit [8,9]. Studies investigating how this loss of function may influence brain responses to
nicotine have given key insights into the mechanisms of nicotine dependence. Specifically, transgenic mice engineered to completely lack expression of a5 nAChR subunits (Chrna5–/– mice) are less sensitive to aversive qualities of nicotine that normally limit intake [10]. This ‘brake’ on nicotine consumption is relayed by neural connections between the medial habenula and the interpeduncular nucleus, which are enriched in a5* nAChRs. Heavy smoking in carriers of the rs16969968 SNP may therefore reflect diminished capacity of a5* nAChRs to stimulate the medial habenulainterpeduncular nucleus pathway and thereby curb nicotine consumption [10,11]. An important caveat to these previous findings is that the Chrna5–/– mice used in these studies completely lack a5 nAChRs, which contrasts with humans who carry the rs16969968 (or other) SNP and express a5* nAChRs with altered function. Hence, it is possible that complete genetic ablation of a5 subunits in Chrna5–/– mice has different outcomes than mutations that more subtly alter a5* nAChRs function. Consequently, animal
models that more faithfully capture the influence of the rs16969968 risk allele in the brains of smokers are needed. As they report in this issue of Current Biology, Forget et al. [12] capitalized on precision gene editing technologies to generate a transgenic rat that expresses the rs16969968 SNP in the Chrna5 gene and show that this manipulation markedly alters addiction-relevant actions of nicotine in the mutant animals (Figure 1). First, Forget et al. [12] used zincfinger nucleases to introduce the rs16969968 SNP into the Chrna5 gene of rats. Using this gene editing approach, they observed little evidence of ‘off-target’ genetic effects, suggesting that the modification was efficacious and accurate. For comparison, they used the same approach to completely ablate the Chrna5 gene in rats, similar to the Chrna5–/– mice described above. As expected, a5 subunits were undetectable in the brains of the rats in which the Chrna5 gene was entirely ablated, although the total amounts of nAChRs detected across multiple brain
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