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Dopamine Neuron’s Repertoire Expands to GABA Release

9 October 2012. A study published online October 3 in Nature provides a novel function for midbrain dopamine neurons: inhibiting their targets through GABA release. Bernardo Sabatini and his team at Boston’s Harvard University used mouse optogenetics to demonstrate that the activation of substantia nigra pars compacta (SNc) dopamine neurons inhibits the firing of striatal projection neurons through release of GABA. Surprisingly, this GABA release is independent of the vesicular GABA transporter (VGAT), but depends on the vesicular monoamine transporter VMAT2.

Although a myriad of neurotransmitters are implicated in schizophrenia, dopamine has been schizophrenia’s first and most enduring culprit. The dopamine hypothesis was originally formulated over 40 years ago (see SRF Hypothesis by Anissa Abi-Dargham), and even today, dysfunctional dopamine neurons remain key players in the positive and negative symptoms of the illness (Howes and Kapur, 2009).

A hyperactive subcortical dopamine system is thought to underlie the psychosis of schizophrenia. Prominent members of the dopamine system within the midbrain include the SNc and ventral tegmental area, regions that are home to the two largest populations of dopamine neurons. These midbrain neurons both project to the striatum and, through dopamine release, activate direct-pathway striatal projection neurons (SPNs) and inhibit indirect-pathway SPNs (Gerfen and Surmeier, 2011). Altered activation of the midbrain has been observed in schizophrenia, and correlates with delusional symptoms (see SRF related news story), and neurochemical imaging studies have reported increases in striatal dopamine synthesis capacity, availability, and release (Howes and Kapur, 2009). However, midbrain dopamine neurons also express neuropeptides, and some release glutamate, suggesting that the activity of these cells may extend beyond dopamine (Chuhma et al., 2004).

Lighting up the midbrain
In the current study, first author Nicolas Tritsch and colleagues expressed the light-activated channelrhodopsin-2 cation channel in SNc dopamine neurons so that blue light could be used to turn on these cells (see SRF related news story). Activation of midbrain dopamine neurons resulted in a hyperpolarization of SPNs that was abolished by a GABAA receptor antagonist, suggesting an involvement of these receptors in the inhibitory response of the dopamine neurons. The researchers next addressed whether the GABAA receptor activation occurred through the recruitment of GABA neurons or more directly through GABA release in the dopamine neurons themselves, finding evidence in support of the latter hypothesis.

Surprisingly, GABA release from dopamine neurons appears to be independent of VGAT, the only known mechanism for loading GABA into synaptic vesicles that is considered to be essential for inhibitory neurotransmission (Wojcik et al., 2006). Elimination of VGAT from dopamine neurons did not alter light-evoked inhibitory current. In addition, deletion of the vesicular glutamate transporter VGLUT2, which loads the GABA precursor glutamate into vesicles, also produced no effect on the light-evoked inhibitory current, ruling out the possibility that GABA synthesis occurs inside vesicles. Interestingly, inhibitory current was eliminated in slices treated with VMAT2 antagonists, suggesting that VMAT2 is required for GABA release from midbrain dopamine neurons. Although VMAT2 is known to transport many neurotransmitters, including dopamine, the current study is the first report of a GABA transporter function.

Taken together, the data from this study suggest a new inhibitory role of dopamine neurons on SPNs that is dependent on VMAT2-mediated packaging of GABA into synaptic vesicles. However, as noted by the authors, the possibility that another neurotransmitter besides GABA acts on GABAA receptors to mediate this effect cannot be excluded. And the fact that VMAT2 is expressed in all monoaminergic neurons suggests that GABA release may extend to other types of neurons. In fact, GABA release from dopamine neurons has been reported in the retina and olfactory bulb (Hirasawa et al., 2009; Maher and Westbrook, 2008). These findings also raise the question of whether the altered GABA synthesis observed in the cortical interneurons of schizophrenia subjects (see SRF related news story) may extend to subcortical dopamine neurons.—Allison A. Curley.

Tritsch NX, Ding JB, Sabatini BL. Dopaminergic neurons inhibit striatal output through non-canonical release of GABA. Nature. 2012 Oct 3. Abstract

Comments on Related News

Related News: Genetics, Expression Profiling Support GABA Deficits in Schizophrenia

Comment by:  Karoly Mirnics, SRF Advisor
Submitted 26 June 2007
Posted 26 June 2007

The evidence is becoming overwhelming that the GABA system disturbances are a critical hallmark of schizophrenia. The data indicate that these processes are present across different brain regions, albeit with some notable differences in the exact genes affected. Synthesizing the observations from the recent scientific reports strongly suggest that the observed GABA system disturbances arise as a result of complex genetic-epigenetic-environmental-adaptational events. While we currently do not understand the nature of these interactions, it is clear that this will become a major focus of translational neuroscience over the next several years, including dissecting the pathophysiology of these events using in vitro and in vivo experimental models.

View all comments by Karoly Mirnics

Related News: Genetics, Expression Profiling Support GABA Deficits in Schizophrenia

Comment by:  Schahram Akbarian
Submitted 26 June 2007
Posted 26 June 2007
  I recommend the Primary Papers

The three papers discussed in the above News article are the most recent to imply dysregulation of the cortical GABAergic system in schizophrenia and related disease. Each paper adds a new twist to the story—molecular changes in the hippocampus of schizophrenia and bipolar subjects show striking differences dependent on layer and subregion (Benes et al), and in prefrontal cortex, there is mounting evidence that changes in the "GABA-transcriptome" affect certain subtypes of inhibitory interneurons (Hashimoto et al). The polymorphisms in the GAD1/GAD67 (GABA synthesis) gene which Straub el al. identified as genetic modifiers for cognitive performance and as schizophrenia risk factors will undoubtedly spur further interest in the field; it will be interesting to find out in future studies whether these genetic variants determine the longitudinal course/outcome of the disease, treatment response etc etc.

View all comments by Schahram Akbarian

Related News: Commentary Brief: Optogenetics Links Interneurons and γ Oscillations

Comment by:  Guillermo Gonzalez-Burgos
Submitted 24 July 2009
Posted 24 July 2009

Blue light, yellow light, and the role of parvalbumin-positive neurons in the pathophysiology of schizophrenia
Parvalbumin (PV)-positive cells are a prominent subtype of GABA neuron that via perisomatic synapses may strongly inhibit pyramidal cell activity (however, see Szabadics et al., 2006). In schizophrenia, PV neurons have reduced levels of mRNA for PV and for GAD67, the 67 kilodalton form of the GABA-synthesizing enzyme glutamate decarboxylase. The functional consequences of the PV reduction in schizophrenia are poorly understood, but one possibility is that decreased PV partially compensates for a deficit in GABA release caused by the GAD67 reduction. PV is a slow Ca2+ buffer, and so decreasing PV in nerve terminals may facilitate GABA release during repetitive PV cell firing (for a review, see Gonzalez-Burgos and Lewis, 2008).

Why is PV cell-mediated inhibition significant to brain function? What deficits in cortical circuit function may be compensated for (at least partially) by a decrease of PV in schizophrenia? The answers to these questions depend on our knowledge of the functional role of PV neurons in cortical circuits. A leading hypothesis in this regard suggests that PV cells are essential for the production of synchronized oscillations in cortex, particularly in the γ frequency band (Bartos et al., 2007). γ oscillations are thought to be important for the transmission of information within and between neocortical areas (Salinas and Sejnowski, 2001). If so, then γ activity must be important for cognition, which is critically dependent on the flow of information across the neocortex (Singer, 1999; Fuster, 2004). Therefore, cognitive deficits (a key feature of schizophrenia) may result from the impairment of γ oscillations reported in the illness, which in turn could be a consequence of deficits in PV cell-mediated inhibition.

How is PV cell-mediated inhibition linked to the production of γ oscillations? PV neurons alone are not sufficient to produce network oscillations because, although PV cell membranes resonate at γ frequency (Pike et al., 2000), PV neurons actually lack intrinsic pacemaker activity. Therefore, whereas PV cells may be necessary to produce γ oscillations, synaptic interactions with other cell types in the cortical circuit must be necessary as well.

Studying the link between PV neuron activity and γ oscillations is complicated by the lack of tools available to selectively manipulate PV cell activity. Interestingly, two recent studies (Sohal et al., 2009; Cardin et al., 2009) employed novel “optogenetic” methods in mice, to further advance our understanding of how PV neurons are involved in γ oscillations.

Using viral vectors to drive cell type-specific expression of recombinant genes, Sohal and colleagues, as well as Cardin et al., produced expression of microbial opsins (which are light-sensitive ion channel proteins) selectively in specific populations of cortical neurons. Briefly described, modulation of neuronal activity using such optogenetic techniques works as follows: in cells expressing channelrhodopsin-2 (ChR2), illumination with blue light produces a depolarizing current that has excitatory effects (increases cell firing). On the other hand, cells expressing halorhodopsin (eNpHR) respond to yellow light with a hyperpolarizing current that has inhibitory effects (decreases cell firing). In this way, light of different wavelengths can be used to either inhibit or excite PV cells or pyramidal (PYR) neurons in the mouse cortex (in vivo or in vitro) in different experimental designs.

Sohal and colleagues first demonstrated that inhibiting the activity of eNpHR-expressing PV neurons with yellow light suppresses γ oscillations generated in vivo by rhythmic flashes of blue light applied to stimulate nearby ChR2-expressing PYR neurons. Furthermore, they show that non-rhythmic excitation of PYR cells produces non-rhythmic PYR cell firing. However, if the non-rhythmic PYR spikes are used to trigger feedback inhibition by PV neurons (driven by blue light flashes that stimulate ChR2-expressing PV cells), the addition of feedback inhibition induces a γ rhythm in PYR cell output. These results show that by means of recurrent interactions with pyramidal cells (consistent with the so-called PING models of γ rhythms; Whittington et al., 2000), PV cell activity is crucial for γ oscillations.

Finally, the experiments performed by Sohal et al. suggest that γ activity may selectively enhance the flow of information in cortical circuits. For example, their experiments demonstrate that the gain of the neuronal input-output relation (that is, the slope of the curve describing the transformation of inputs into outputs) is specifically enhanced when excitatory inputs onto a PYR cell are modulated rhythmically at γ frequency. Moreover, the amount of information flowing across synapses during interactions between PYR and PV neurons was estimated using concepts derived from information theory. The estimates from Sohal et al. showed that when network activity was driven by trains of blue flashes delivered at γ frequency, information transmission was markedly enhanced.

Using somewhat different genetic engineering approaches, Cardin and colleagues produced cell type-specific expression of ChR2 in PV cells or PYR neurons. Expression of ChR2 in PV cells of the mouse barrel (somatosensory) cortex allowed the activation of PV neurons with rhythmic flashes of light. Such manipulation produced rhythmic population activity (as detected recording local field potentials) more strongly when PV cells were driven at γ frequency compared with other frequencies. They report, in addition, some data showing that manipulation of PV cell activity has an impact on γ oscillations intrinsically generated by the cortical circuits, as opposed to γ rhythms induced by rhythmic stimuli applied by the investigators. For example, brief flashes of blue light applied to stimulate firing of ChR2-expressing PV neurons during spontaneous γ activity were able to reset the phase of the γ rhythm. Cardin et al. also demonstrate that activation of ChR2-expressing PV neurons can suppress the somatosensory response (to whisker stimulation) of nearby PYR cells. Then they go on to test an important functional role predicted for γ oscillations: that cells in a local network engaged in γ oscillations may respond differently to incoming inputs, depending on the timing of the incoming inputs relative to the phase of the γ cycle (Fries et al., 2007). In an elegant experiment, the investigators paired brief whisker stimulation with rhythmic flashes of blue light which, by stimulating ChR2-expressing PV cells, generate a γ rhythm locally. The crucial finding from this experiment is that the excitatory power of whisker stimulation was strongly dependent on the γ cycle phase at which whisker stimulation was delivered.

The data from these two recent studies briefly summarized above further consolidate the notion that PV-positive GABA neurons are key players in the mechanisms of γ synchrony in cortex. The data from these studies confirm that rhythmic PV neuron firing at γ frequency is sufficient to generate a γ rhythm in the population of postsynaptic neurons. This is not the same, however, as saying that PV neurons alone are sufficient to generate γ. Indeed, the data from these two studies point to the idea that PV neurons work in close interaction, via feedback loops, with nearby pyramidal cells. This makes sense, given that PV neurons are not intrinsic pacemakers. γ rhythms, therefore, seem to originate in complex network interactions that require the coordinated activity of pyramidal neurons, PV cells, and possibly other GABA neuron subtypes as well.

These two studies also highlight the similar importance of PV cell-dependent γ oscillations across different regions of cortex primarily involved in very different functions: Sohal and colleagues studied the role of PV neurons in frontal cortical areas, whereas Cardin et al. manipulated PV cell activity in the primary somatosensory cortex. The similarity of the findings regarding PV neuron function suggests that these neurons probably play a very similar role, at the microcircuit level, in these two very different cortical areas. Interestingly, deficits in GABA transmission, as assessed in postmortem brain studies, appear to be found in multiple areas of cortex simultaneously (Hashimoto et al., 2008). If this is indeed the case, then an impairment of γ oscillations may be present in most cortical areas. Thus, deficits in PV cell-dependent γ rhythms may explain the impairment of not only complex cognitive functions (for example, working memory), but also of more basic sensory processing which, as reviewed elsewhere (Javitt, 2009), is also impaired in schizophrenia. Finding a global deficit of GABA transmission and γ oscillations, as opposed to a deficit restricted to a single cortical area, increases the probability of success in developing pharmacological treatments.

A better understanding of the functional role of PV neurons in normal cortical circuits is crucial to developing better models that could explain how alterations of PV cells (and of other GABA neurons subtypes) originate in schizophrenia. As highlighted elsewhere (Lewis and Gonzalez-Burgos, 2008), any given alteration observed in schizophrenia may represent 1) cause, an upstream factor related to the disease pathogenesis; 2) consequence, a deleterious effect of a cause; 3) compensation, a response to either cause or consequence that helps restore homeostasis; or 4) confound, a product of factors frequently associated with, but not a part of, the disease process, or an artifact of the approach used to obtain the measure of interest. A major challenge for schizophrenia research is therefore determining to which of the four “C” categories each alteration belongs (Lewis and Gonzalez-Burgos, 2008). Certainly, information from basic neuroscience research studies such as those of Sohal et al. and Cardin et al. and many other past and future studies is extremely helpful in achieving this goal.


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View all comments by Guillermo Gonzalez-Burgos