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Enregistrement W3159612192 · doi:10.1111/ejn.15268

The challenging diversity of neurons in the ventral tegmental area: A commentary of Miranda‐Barrientos, J. et al., <i>Eur J Neurosci</i> 2021

2021· article· en· W3159612192 sur OpenAlexaff
Charles Ducrot, Louis‐Éric Trudeau

Notice bibliographique

RevueEuropean Journal of Neuroscience · 2021
Typearticle
Langueen
DomaineNeuroscience
ThématiqueNeuroscience and Neuropharmacology Research
Établissements canadiensUniversité de Montréal
Organismes subventionnairesnon disponible
Mots-clésDiversity (politics)Library scienceMedicineSociologyAnthropology

Résumé

récupéré en direct d'OpenAlex

In 1992, a landmark paper by Johnson and North published in the Journal of Physiology and entitled "Two types of neurone in the rat ventral tegmental area (VTA) and their synaptic inputs" (Johnson & North, 1992) provided a first glimpse of the diversity of neurons in this part of the brain. The VTA area was initially better known for the presence of dopamine (DA)-containing neurons projecting to the ventral striatum and for its key role in motivated behaviors and drug addiction. The work by Johnson and North revealed the existence of two distinct categories of neurons that they named "principal cells" and "secondary cells." Principal cells were described as pacemaking neurons with broad action potentials and showing a marked hyperpolarizing response to DA. In contrast, secondary cells were identified as typically quiescent neurons that are hyperpolarized by opioid peptides. The authors concluded that, similarly to the substantia nigra, the VTA thus contained neurons releasing either DA or GABA. Since this paper, work by several teams has considerably expanded our knowledge of neuronal diversity in this brain region. With the discovery of glutamate release and the expression of the type-2 vesicular glutamate transporter (VGLUT2) by subpopulations of DA neurons (Sulzer et al., 1998; Dal Bo et al., 2004), it became obvious that the complexity of the VTA was underestimated. The team of Marisela Morales has since made major contributions to this field by mapping the distribution of neurons with mixed neurotransmitter phenotype in the mesencephalon and by using anatomical tools, optogenetics, and behavioral tasks to examine some of the roles of these neurons (Li et al., 2013; Mongia et al., 2019; Morales & Margolis, 2017; Qi et al., 2016; Root et al., 2014, 2018; Wang et al., 2015; Yamaguchi et al., 2007, 2011, 2013, 2015). In this issue of the European Journal of Neuroscience, Miranda-Barientos and colleagues provide new data that further expand our knowledge of the diversity of neurons in the VTA. In their paper entitled "VTA GABA, glutamate, and glutamate-GABA neurons are heterogeneous in their electrophysiological and pharmacological properties" (Miranda-Barrientos et al., 2021), they took advantage of new intersectional genetic tools to differentially label subsets of neurons using a vglut2-Cre/vgat-Flp mouse (VGAT or VIAAT is the vesicular GABA/glycine transporter). Combining this approach to patch-clamp electrophysiology and the use of a mu-opioid receptor agonist, the authors report that contrarily to what was known in the early 1990s at the time of the paper by Johnson and North, some VTA glutamatergic neurons, like GABA neurons, are hyperpolarized by mu-opioid receptor ligands. Miranda-Barientos and colleagues also reveal additional diversity in the electrophysiological properties of glutamate, GABA, and mixed glutamate/GABA neurons of the VTA. An original contribution of the paper by Miranda-Barientos et al. is the use of intersectional genetic tools. A major goal in neuroscience is to understand how different neuronal cell types contribute to physiological brain functions and to brain diseases. An ever-increasing range of genetic tools is becoming available to help neuroscientists reach these goals. An emerging strategy based on the control of gene expression by the use of recombinase enzymes is the INTRSECT (for "intronic recombinase sites enabling combinatorial targeting") approach that uses Cre-, Dre-, and Flp recombinases acting on gene target sites termed LoxP, ROX, and FRT, respectively (Anastassiadis et al., 2009; Fenno et al., 2014, 2020; Ramírez-Solis et al., 1995; Sadowski, 1995). The Cre-LoxP and Flp-FRT systems are presently the most broadly used. Gene excision, inversion, or translocation can be driven by the orientation of the LoxP or FRT sites in specific cellular sub-populations. Miranda-Barientos et al. (2021) used a vglut2-Cre/vgat-Flp transgenic mouse and strereotaxic injection of Cre- and/or Flp-dependent viral vectors to label VTA neurons with fluorescent proteins. This allowed to identify recorded neurons as putative glutamate, GABA, or mixed glutamate/GABA neurons. In this work, the authors closely examined how opioid receptors modulate the activity of VTA neurons. Opioids compounds bind to Mu (µ), Delta (d) or Kappa (k; MOR, DOR, KOR, respectively) receptors. The opioid system is fundamental for pain modulation but is also involved in a range of other physiological mechanisms. MOR agonists produce positive motivational actions through excitation of VTA DA neurons via direct and indirect mechanisms (Bonci & Williams, 1997; Bozarth & Wise, 1981; Johnson & North, 1992; Margolis et al., 2014; Olmstead & Franklin, 1997). Activation of MORs on local GABA neurons in the VTA reduces the frequency of inhibitory postsynaptic currents in DA neurons, leading to an increase of their excitability (Johnson & North, 1992) and increased DA release in the nucleus accumbens (Di Chiara & Imperato, 1988). The subcellular expression and distribution of MOR is critical for understanding neural circuits and mechanisms involved in the effect of opioids (Le Merrer et al., 2009). In the VTA, it is well established that MORs are localized in the presynaptic and postsynaptic compartment of GABA neurons (Bergevin et al., 2002; Galaj et al., 2020; Margolis et al., 2012). Miranda-Barientos et al. add to this body of knowledge by showing that MORs are expressed by most GABA neurons that are negative for VGluT2 (VGluT2−/VGaT+ neurons) as well as glutamatergic neurons that are negative for VGaT (VGluT2+/VGaT− neurons). Interestingly, neurons co-releasing GABA and glutamate (VGluT2+/VGaT+) do not express MOR. They also show that VGluT2−/VGaT+neurons and VGluT2+/VGaT− neurons are postsynaptically inhibited by DAMGO (a synthetic opioid peptide activating MORs). Further experiments will be required to integrate these new findings in an improved model of how opioids act in the VTA in physiological and pathological contexts. The present work focused on a comparison of glutamate, GABA and mixed glutamate/GABA neurons in the mouse VTA. However, the authors did not compare the electrophysiological properties of these neuronal populations with those of mixed DA/glutamate neurons. They also did not determine whether GABA and/or glutamate neurons from the VTA also contain other neurotransmitters including neuropeptides such as CCK or neurotensin that are heterogeneously found in subsets of DA and non-DA neurons in the ventral midbrain. These are just a few examples of the growing complexity and challenges of such studies, something that is only bound to accelerate with the use of approaches such as single-cell RNASeq. Going forward, a major challenge will be the integration of these findings in a unified vision of the physiological and the pathophysiological functions of these "multilingual" neurons (Trudeau et al., 2014). The peer review history for this article is available at https://publons.com/publon/10.1111/ejn.15268. Data relating to the experiments are available upon request.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,011
score de la tête « metaresearch » (Gemma)0,023
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Commentaire · Signal consensuel: Commentaire
Score de désaccord entre enseignants0,029
Score d'incertitude au seuil0,059

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0110,023
Méta-épidémiologie (sens strict)0,0020,001
Méta-épidémiologie (sens large)0,0030,002
Bibliométrie0,0030,002
Études des sciences et des technologies0,0050,013
Communication savante0,0070,012
Science ouverte0,0070,004
Intégrité de la recherche0,0290,056
Charge utile insuffisante (le modèle a refusé de juger)0,0020,003

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,075
Tête enseignante GPT0,324
Écart entre enseignants0,249 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreCommentaire

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations1
Publié2021
Routes d'admission1
Résumé présentoui

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