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Dispatches feedback mediated by redox balance [18] or metabolic intermediates, including phosphoenolpyruvate. Another feedback loop might rely on changes in the Mal synthesis intermediate oxaloacetate, which has been shown to regulate guard cell anion channels [19] and is also transported efficiently across the chloroplast envelope [20]. Regardless of the answer, the study leaves no doubt about the importance of starch and sugar metabolism in accelerating stomatal opening, and is certain to stimulate research into its integration with membrane transport in the guard cell model.
REFERENCES
5. Roelfsema, M.R.G., and Hedrich, R. (2005). In the light of stomatal opening: new insights into ‘the Watergate’. New Phytol. 167, 665–691. 6. Cutler, S.R., Rodriguez, P.L., Finkelstein, R.R., and Abrams, S.R. (2010). Abscisic acid: emergence of a core signaling network. Annu. Rev. Plant Biol. 61, 651–679. 7. Lawson, T., and Blatt, M.R. (2014). Stomatal size, speed, and responsiveness impact on photosynthesis and water use efficiency. Plant Phys. 164, 1556–1570. 8. Hills, A., Chen, Z.H., Amtmann, A., Blatt, M.R., and Lew, V.L. (2012). OnGuard, a computational platform for quantitative kinetic modeling of guard cell physiology. Plant Phys. 159, 1026–1042. 9. Chen, Z.H., Hills, A., Baetz, U., Amtmann, A., Lew, V.L., and Blatt, M.R. (2012). Systems dynamic modeling of the stomatal guard cell predicts emergent behaviors in transport, signaling, and volume control. Plant Phys. 159, 1235–1251. 10. Talbott, L.D., and Zeiger, E. (1993). Sugar and organic acid accumulation in guard cells of Vicia faba in response to red and blue light. Plant Phys. 102, 1163–1169.
1. Berry, J.A., Beerling, D.J., and Franks, P.J. (2010). Stomata: key players in the earth system, past and present. Curr. Opin. Plant Biol. 13, 233–240. 2. MacRobbie, E.A.C. (1981). Effects of ABA in isolated guard cells of Commelina communis L. J. Exp. Bot. 32, 563–572.
11. MacRobbie, E.A.C., and Lettau, J. (1980). Ion content and aperture in isolated guard cells of Commelina communis L. J. Membrane Biol. 53, 199–205.
3. Blatt, M.R. (1990). Potassium channel currents in intact stomatal guard cells: rapid enhancement by abscisic acid. Planta 180, 445–455.
12. Van Kirk, C.A., and Raschke, K. (1978). Presence of chloride reduces malate production in epidermis during stomatal opening. Plant Phys. 61, 361–364.
4. Blatt, M.R., and Armstrong, F. (1993). K + channels of stomatal guard cells: abscisic acid-evoked control of the outward rectifier mediated by cytoplasmic pH. Planta 191, 330–341.
13. Raschke, K., and Schnabl, H. (1978). Availability of chloride affects balance between potassium chloride and potassium malate in guard cells of Vicia faba L. Plant Phys. 62, 84–87.
14. Horrer, D., Flu¨tsch, S., Pazmino, D., Matthews, J.S.A., Thalmann, M., Niegro, A., Leonhardt, N., Lawson, T., and Santelia, D. (2016). Blue light induces a distinct starch degradation pathway in guard cells for stomatal opening. Curr. Biol. 26, 362–370. 15. Christie, J.M., Blackwood, L., Petersen, J., and Sullivan, S. (2015). Plant flavoprotein photoreceptors. Plant Cell Phys. 56, 401–413. 16. Ueno, K., Kinoshita, T., Inoue, S., Emi, T., and Shimazaki, K. (2005). Biochemical characterization of plasma membrane H + -ATPase activation in guard cell protoplasts of Arabidopsis thaliana in response to blue light. Plant Cell Phys. 46, 955–963. 17. Merlot, S., Leonhardt, N., Fenzi, F., Valon, C., Costa, M., Piette, L., Vavasseur, A., Genty, B., Boivin, K., Mueller, A., et al. (2007). Constitutive activation of a plasma membrane H + -ATPase prevents abscisic acid-mediated stomatal closure. EMBO J. 26, 3216–3226. 18. Seung, D., Thalmann, M., Sparla, F., Abou Hachem, M., Lee, S.K., Issakidis-Bourguet, E., Svensson, B., Zeeman, S.C., and Santelia, D. (2013). Arabidopsis thaliana AMY3 Is a unique redox- regulated chloroplastic alpha-amylase. J. Biol. Chem. 288, 33620–33633. 19. Wang, Y., and Blatt, M.R. (2011). Anion channel sensitivity to cytosolic organic acids implicates a central role for oxaloacetate in integrating ion flux with metabolism in stomatal guard cells. Biochem. J. 439, 161–170. 20. Kinoshita, H., Nagasaki, J., Yoshikawa, N., Yamamoto, A., Takito, S., Kawasaki, M., Sugiyama, T., Miyake, H., Weber, A.P.M., and Taniguchi, M. (2011). The chloroplastic 2-oxoglutarate/malate transporter has dual function as the malate valve and in carbon/ nitrogen metabolism. Plant J. 65, 15–26.
Neural Plasticity: Dopamine Tunes the Mushroom Body Output Network Scott Waddell Centre for Neural Circuits and Behaviour, The University of Oxford, Tinsley Building, Mansfield Road, Oxford, OX1 3SR, UK Correspondence:
[email protected] http://dx.doi.org/10.1016/j.cub.2015.12.023
Two recent studies in Drosophila provide evidence that dopamine can drive synaptic depression and facilitation, supporting models in which learning and the behavioral state of the fly guide behavior by tuning mushroom body output synapses. It has become increasingly apparent over the last few years that the dopaminergic systems of insects and mammals have analogous roles [1]. Several studies in the numerically simpler Drosophila brain have
together established that reinforcement and motivational control are provided by different subsets of dopaminergic neurons that innervate anatomically discrete zones within the mushroom body
lobes of the fly central nervous system (Figure1) [2–7]. Each of these zones has a corresponding mushroom body output neuron, activation of which favors either approach or avoidance behavior [8,9].
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Dispatches Kenyon cell
Satiety
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Figure 1. Experience is represented as dopaminergic modulation of Kenyon cell synapses in mushroom body output neuron compartments. An individual g Kenyon cell (black) sends a process through adjacent zones of the g lobe where it forms en passant synapses with largely compartment-specific mushroom body output neurons (blue). Each zone has a corresponding set of modulatory dopaminergic neurons (green) whose presynaptic terminals, and therefore likely released dopamine, are largely restricted to that zone. Some additional complexity of dopaminergic neurons and mushroom body output neurons that innervate and connect multiple compartments are indicated (grey). Reinforcing stimuli such as water, sugar, electric shock, heat and bitter taste, and behavioral states such as satiety, ‘flailing’ and sedation positively regulate specific classes of dopaminergic neurons while simultaneously inhibiting others (not illustrated). Individual mushroom body output neurons release either GABA, acetylcholine (ACh), glutamate (Glu) or an unknown neurotransmitter. Their activation can promote either approach or avoidance and sleep or wake behaviors. Dopaminergic neurons can be thought of as functioning like the fingers of a piano player to depress or release combinations of mushroom body output neuron channels and therefore skew the overall flow through the network.
During learning, dopaminergic neurons alter the relative odor-drive from the Kenyon cells of the mushroom body to collections of mushroom body output neurons [9,10], suggesting a model in which plasticity skews the overall mushroom body output neuron network to direct appropriate behavior [9,11].
Two recent studies [12,13] used synthetic activation of dopaminergic neurons to determine how dopamine release regulates synaptic activity through the mushroom body network. Dopaminergic neurons that innervate discrete zones of the horizontal lobes, and particularly the gamma lobes, of
the mushroom bodies have been implicated in learned and innate odordriven behaviors (Figure 1) [3–7,14,15]. Dopaminergic neurons innervating the g1 region are required to reinforce learning with multiple negative stimuli, and pairing odor presentation with g1, g2 or g3 dopaminergic neuron activation can drive aversive olfactory learning [3]. In contrast, g4 dopaminergic neurons are required for learning with water reward in thirsty flies [6], whereas g5 dopaminergic neurons are critical for nutritious sucrose reinforcement in hungry flies [7]. Pairing artificial activation of g4 or g5 dopaminergic neurons with odor presentation forms odor approach memories. Using a living fly preparation and electrophysiological recordings, Hige et al. [12] monitored learning-relevant plasticity in odor-evoked responses in the g1 mushroom body output neuron. They found that pairing odor presentation with optogenetic activation of the g1 dopaminergic neurons drove a near 80% reduction in the odor-evoked response of the g1 mushroom body output neuron, but not in the neighboring g2 mushroom body output neuron. Importantly, the depression was odor-specific and the plasticity followed the same temporal rules as behavioral learning. In addition, plasticity could be induced when spiking activity was suppressed in the postsynaptic g1 mushroom body output neuron, providing strong evidence that spike-timing dependent plasticity is not essential, at least at this Kenyon cell–mushroom body output neuron connection. This is consistent with learning being coded as dopamine driven presynaptic plasticity at Kenyon cell– mushroom body output neuron junctions [11], although there may be different rules for inducing plasticity in other mushroom body output neuron zones [12]. In the second recent study, Cohn et al. [13] used a presynaptically localized GCaMP calcium sensor [16] to analyse the activity of dopaminergic neurons, Kenyon cells and mushroom body output neurons in living flies and dissected fly brains. Liveimaging dopaminergic neuron projections revealed that wet sugar activated g4 and g5 rewarding dopaminergic neurons, as expected [6,7], but also reduced activity of aversive dopaminergic neurons. In comparison, shock delivery activated
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Dispatches g2 and g3 dopaminergic neurons, while driving a relative inhibition of g4 and g5 dopaminergic neurons. These coordinated opponent responses support prior anatomical work which suggested interconnectivity within the dopaminergic neuron network [17]. Testing functional connectivity by activating mushroom body output neurons in one compartment while imaging dopaminergic neuron responses revealed a more complex interaction than reciprocal inhibition between the g2/g3 and g4/g5 dopaminergic neuron compartments [13]. The consequence of dopaminergic neuron activation on the Kenyon cell– mushroom body output neuron network was assessed following unpaired stimulation of either the rewarding or aversive dopaminergic neurons. Activation of a population of rewarding dopaminergic neurons potentiated spontaneous and Kenyon cell-evoked responses in the relevant g4 mushroom body output neurons, measured with either electrophysiology or presynaptically localized GCaMP. Similarly, activation of the aversive dopaminergic neurons potentiated Kenyon cell-evoked responses in the g2 mushroom body output neurons. Cohn et al. [13] also paired Kenyon cell stimulation with dopaminergic neuron activation in a dissected brain, or odor with dopaminergic neuron activation in a live fly. Consistent with the results of Hige et al. [12], these paired protocols caused a depression in evoked mushroom body output neuron calcium. Dopaminergic neuron activity can therefore drive bidirectional, compartment-restricted Kenyon cell–mushroom body output neuron plasticity [12,13], consistent with earlier work [9,10]. Ongoing dopaminergic neuron activity in the g1 compartment of the mushroom body has been suggested to reduce the motivational salience of odors to suppress expression of food-relevant memories in satiated flies [5]. Furthermore dopaminergic neurons innervating the g0 lobe provide thirst-dependent control of water seeking [6] and hungerdependent control of CO2 directed behavior [14]. It is therefore plausible that ongoing activity in dopaminergic neurons provides a moment-by-moment update of elements of the behavioral
state of the fly and reconfigures the Kenyon cell–mushroom body output neuron network accordingly [11]. In support of such a model, Cohn et al. [13] noted coordinated dopaminergic neuron activation in the absence of reinforcer delivery. Aversive g2/g3 dopaminergic neuron activity accompanied ‘flailing’ movement in a dangling tethered fly, whereas the rewarding g4/g5 dopaminergic neurons were active when the flies were still. The patterns of dopaminergic neuron activity were not so correlated and logical when flies walked on a rotating ball. Olfactory stimuli also evoked patterned dopaminergic neuron activity, as would be expected from Kenyon cell–mushroom body output neuron-dopaminergic neuron connectivity [17]. If combinations of dopaminergic neurons provide ongoing modulation to the mushroom bodies, one might predict that this would be evident at the level of Kenyon cell and mushroom body output neuron activity. Interestingly, odors were shown to evoke more presynaptic calcium in Kenyon cells and mushroom body output neurons in the proximal g2/g3 compartments than the distal g4/g5 zones. Furthermore, a more uniform Kenyon cell signal was apparent in a dissected brain, and in a dopamine receptor mutant [13], consistent with in vivo dopaminergic modulation tuning combinations of Kenyon cell–mushroom body output neuron compartments. It will be important to understand how ongoing and stimulusevoked dopamine signals interact in the fly brain. One would expect that dopaminergic neurons shift between tonic and phasic firing states. In addition, it appears that different dopamine receptors are required for statedependent modulation [13] and reinforcement [18]. It is currently unclear how ongoing dopaminergic neuron activity is generated. Movement itself, or sensory processes associated with it, could drive certain dopaminergic neurons to provide an update of the fly’s situation. It will be interesting to know how Kenyon cell activity changes along the gamma neuron arbor as the fly transitions from quiescence to moving. It also seems possible that dopaminergic neuron activity might reflect Stop/Go signaling of locomotor intent like it
does in the mammalian striatum [19]. Many years ago, the mushroom body was shown to influence the lengths of locomotor bouts [20]. Furthermore, activation of g4/g5 outputs has been reported to promote waking activity, whereas g2/g3 stimulation favors sleep [8]. The recent studies [12,13] strengthen the evidence that the fly dopaminergic system is functionally analogous to that of mammals. Drosophila dopaminergic neurons, like their mammalian counterparts, respond in a bidirectional manner to positive and negative stimuli. Furthermore, roles for dopaminergic neurons in the mushroom body in motivated behavior, reinforcement learning and movement parallel those of dopaminergic neurons in the basal ganglia. The reduced anatomical complexity and the ability to monitor physiological changes in identified neurons suggests that studies in the fly will provide a detailed cellular-level network understanding of how dopaminergic neurons select mushroom body circuit configurations to control behavior. REFERENCES 1. Waddell, S. (2013). Reinforcement signalling in Drosophila; dopamine does it all after all. Curr. Opin. Neurobiol. 23, 324–329. 2. Claridge-Chang, A., Roorda, R.D., Vrontou, E., Sjulson, L., Li, H., Hirsh, J., and Miesenbock, G. (2009). Writing memories with lightaddressable reinforcement circuitry. Cell 139, 405–415. 3. Aso, Y., Herb, A., Ogueta, M., Siwanowicz, I., Templier, T., Friedrich, A.B., Ito, K., Scholz, H., and Tanimoto, H. (2012). Three dopamine pathways induce aversive odor memories with different stability. PLoS Genet. 8, e1002768. 4. Burke, C.J., Huetteroth, W., Owald, D., Perisse, E., Krashes, M.J., Das, G., Gohl, D., Silies, M., Certel, S., and Waddell, S. (2012). Layered reward signalling through octopamine and dopamine in Drosophila. Nature 492, 433–437. 5. Krashes, M.J., DasGupta, S., Vreede, A., White, B., Armstrong, J.D., and Waddell, S. (2009). A neural circuit mechanism integrating motivational state with memory expression in Drosophila. Cell 139, 416–427. 6. Lin, S., Owald, D., Chandra, V., Talbot, C., Huetteroth, W., and Waddell, S. (2014). Neural correlates of water reward in thirsty Drosophila. Nat. Neurosci. 17, 1536–1542. 7. Huetteroth, W., Perisse, E., Lin, S., Klappenbach, M., Burke, C., and Waddell, S. (2015). Sweet taste and nutrient value subdivide rewarding dopaminergic neurons in Drosophila. Curr. Biol. 25, 751–758.
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Dispatches 8. Aso, Y., Sitaraman, D., Ichinose, T., Kaun, K.R., Vogt, K., Belliart-Guerin, G., Placais, P.Y., Robie, A.A., Yamagata, N., Schnaitmann, C., et al. (2014). Mushroom body output neurons encode valence and guide memorybased action selection in Drosophila. eLife 3, e04580. 9. Owald, D., Felsenberg, J., Talbot, C.B., Das, G., Perisse, E., Huetteroth, W., and Waddell, S. (2015). Activity of defined mushroom body output neurons underlies learned olfactory behavior in Drosophila. Neuron 86, 417–427. 10. Sejourne, J., Placais, P.Y., Aso, Y., Siwanowicz, I., Trannoy, S., Thoma, V., Tedjakumala, S.R., Rubin, G.M., Tchenio, P., Ito, K., et al. (2011). Mushroom body efferent neurons responsible for aversive olfactory memory retrieval in Drosophila. Nat. Neurosci. 14, 903–910. 11. Owald, D., and Waddell, S. (2015). Olfactory learning skews mushroom body output pathways to steer behavioral choice in
Drosophila. Curr. Opin. Neurobiol. 35, 178–184. 12. Hige, T., Aso, Y., Modi, M.N., Rubin, G.M., and Turner, G.C. (2015). Heterosynaptic plasticity underlies aversive olfactory learning in Drosophila. Neuron 88, 985–998. 13. Cohn, R., Morantte, I., and Ruta, V. (2015). Coordinated and compartmentalized neuromodulation shapes sensory processing in Drosophila. Cell 163, 1742–1755. 14. Lewis, L.P., Siju, K.P., Aso, Y., Friedrich, A.B., Bulteel, A.J., Rubin, G.M., and Grunwald Kadow, I.C. (2015). A higher brain circuit for immediate integration of conflicting sensory information in Drosophila. Curr. Biol. 25, 2203– 2214. 15. Keleman, K., Vrontou, E., Kruttner, S., Yu, J.Y., Kurtovic-Kozaric, A., and Dickson, B.J. (2012). Dopamine neurons modulate pheromone responses in Drosophila courtship learning. Nature 489, 145–149.
16. Dreosti, E., Odermatt, B., Dorostkar, M.M., and Lagnado, L. (2009). A genetically encoded reporter of synaptic activity in vivo. Nat. Methods 6, 883–889. 17. Aso, Y., Hattori, D., Yu, Y., Johnston, R.M., Iyer, N.A., Ngo, T.T., Dionne, H., Abbott, L.F., Axel, R., Tanimoto, H., et al. (2014). The neuronal architecture of the mushroom body provides a logic for associative learning. eLife 3, e04577. 18. Kim, Y.C., Lee, H.G., and Han, K.A. (2007). D1 dopamine receptor dDA1 is required in the mushroom body neurons for aversive and appetitive learning in Drosophila. J. Neurosci. 27, 7640–7647. 19. Jin, X., and Costa, R.M. (2010). Start/stop signals emerge in nigrostriatal circuits during sequence learning. Nature 466, 457–462. 20. Martin, J.R., Ernst, R., and Heisenberg, M. (1998). Mushroom bodies suppress locomotor activity in Drosophila melanogaster. Learn. Mem. 5, 179–191.
Bacterial Speciation: Genetic Sweeps in Bacterial Species Frederick M. Cohan Department of Biology, Wesleyan University, Middletown, CT 06459, USA Correspondence:
[email protected] http://dx.doi.org/10.1016/j.cub.2015.10.022
One theory of bacterial speciation states that bacterial and animal species share the property of cohesion, meaning that diversity within a species is constrained. A new study provides direct evidence that genomewide sweeps can limit diversity within bacterial species. ‘‘Anything found to be true of E. coli must also be true of elephants!’’ While Jacques Monod was thinking about the unity of biochemistry, evolutionary biologists and ecologists have also sought unifying principles across all of life. Accordingly, some evolutionary ecologists have proposed universal principles for the origin and nature of species [1–3]. One particularly contentious claim is that across all of life, species are each ‘cohesive’, in the sense that the diversity within each species is constrained by some force [1,2]. Bacterial species may be subject to a special force of cohesion, owing to their low frequency of recombination [4]. This force is periodic selection, where natural selection favoring any adaptive mutation purges the genetic diversity, genome-wide, within an
ecologically homogeneous species or ecotype (Figure 1A,B) [5]. However, whether periodic selection occurs widely in nature or is even possible has been debated with a passion unusual for the field of microbiology [6–8]. Contributing to the uncertainty is that genome-wide sweeps were never observed in nature, that is, until the recent work of Bendall et al. [9] — using a high-throughput, metagenomic approach to survey a bacterial community over time, these authors charted a genome-wide sweep within one natural bacterial population. In the days before metagenomics, it never seemed a good bet to search for a periodic selection event by focusing on your favorite organism — this process was thought too infrequent to be observed in one population during
one grant-funding period. However, what is unlikely to be seen within a single focus population becomes eminently palpable within some population when you can observe an entire community simultaneously. The magic of metagenomics! Bendall et al. [9] surveyed the bacteria of Trout Bog Lake, Wisconsin, over eight years. From each small volume of lake water sampled, they lysed the cells and produced short DNA sequences representing the community’s diversity. Short sequences were assembled into longer sequences by joining sequences (from different organisms) that were homologous and less than 2% divergent from one another. The researchers thereby clustered the organisms into groups of close relatives, and at the same
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