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Enregistrement W2019613619 · doi:10.1113/jphysiol.2012.249573

Matchmaking: SK channels, C‐boutons and motor units

2013· letter· en· W2019613619 sur OpenAlexaff
Robert M. Brownstone, Philippe Magown

Notice bibliographique

RevueThe Journal of Physiology · 2013
Typeletter
Langueen
DomaineNeuroscience
ThématiqueNeurobiology and Insect Physiology Research
Établissements canadiensDalhousie University
Organismes subventionnairesnon disponible
Mots-clésNeurosciencePostsynaptic potentialCholinergicMotor neuronMotor unitBiologyAnatomySpinal cord

Résumé

récupéré en direct d'OpenAlex

For several decades, there has been much fascination with the large cholinergic boutons that form synapses on spinal motoneurons. These boutons are associated with motoneuron subsurface cisterns and hence are called C-boutons. In recent years, several groups have been studying the anatomy and physiology of these relatively large synapses that densely innervate the somata and proximal dendrites of α-motoneurons. For example, we have learned about some molecules clustered in the membrane at the postsynaptic site (mAChR2, Kv2.1), and that these synapses can increase motoneuronal excitability by reducing the post-spike afterhyperpolarisation (AHP; Miles et al. 2007). This leads to an increase in motoneuron firing rate and hence an increase in muscle contraction force. Now, in this issue of The Journal of Physiology, the work by Deardorff et al. (2013) adds to this understanding by showing that two subtypes of channels responsible for the AHP are also clustered at this site, and that different types of motoneurons have different complements of these subtypes. This opens the door to the future possibility of understanding differences between fast and slow motoneurons from a molecular point of view during development and injury. In motoneurons, the AHP functions to limit the maximum rate of firing and to reduce variability in inter-spike intervals. The duration of the AHP following a single action potential differs between motoneurons, and is correlated to the type of muscle fibre innervated by that particular motoneuron (Bakels and Kernell, 1993). Motoneurons that innervate the fastest twitch fibres have the shortest AHPs, thus allowing them to fire at higher rates than those innervating slow twitch fibres, which have longer duration AHPs. In other words, the AHP of a given motoneuron is matched to the contractile speed of the muscle fibre type it innervates. However, the molecular basis underlying the differences in AHP durations and the matching of motoneuron and muscle properties remain unresolved. Now, Deardorff and colleagues beautifully demonstrate that in addition to mAChR2 receptors and KV2.1 channels, SK channels – small conductance calcium-activated potassium channels responsible for the AHP – cluster at C-boutons. They demonstrate in breath-taking images that SK channels, in fact, interdigitate with KV2.1 channels at these synaptic sites. Furthermore, although both SK2 and SK3 channels are seen in this location in all cat and smaller rodent α-motoneurons, larger mouse and rat motoneurons do not express SK3. Through in vivo intracellular recordings in adult rats, they demonstrate that motoneurons lacking SK3 channel clusters have shorter duration AHPs. It thus seems probable that the relative proportion of SK2 and SK3 channels controls the overall AHP duration, with SK3 channels lengthening the AHP duration. This SK isoform distribution would then phenomenologically account for the match between motoneuron and muscle properties. Of course, many questions remain unanswered. There is a third isoform of apamin-sensitive SK channels, SK1, but their expression in motoneurons is not known. It has been shown that in HEK cells, SK1 proteins can interact with both SK2 and SK3 proteins and modulate channel properties and channel trafficking to the cell membrane (Monaghan et al. 2004). Furthermore, it is not known how mAChR2 activation at C-bouton synapses leads to a reduction in AHP or how different motoneuron types respond to this activation. Interestingly, the behavioural deficit noted in mice lacking functional C-boutons was more apparent in swimming than in walking mice (Zagoraiou et al. 2009). Swimming may require a steeper recruitment gain in motor pools (Hultborn et al. 2004), leading to earlier and greater recruitment of fast motoneurons and fast-twitch muscle fibres. In that case, might differential modulation of SK2 and SK3 channels via mAChR2 activation alter this gain to result in greater force production? As to why these channels are clustered at synaptic sites, we might suppose that their function depends on tight control of calcium nanodomains, which may be regulated by subsurface cisterns. But how do these molecules all coalesce at this site? Presumably, there are as yet unidentified scaffolding complexes. Interestingly, as demonstrated in this paper, KV2.1 channels at sites distant to C-bouton synapses are not associated with SK channels, indicating that there may be different mechanisms that anchor these proteins to particular sites. We would expect that in the near future, additional molecules will be discovered that will shed light on the clustering process and the regulation of local calcium activity. Furthermore, how are motoneuron properties matched to the properties of the muscle fibres they innervate – which is the chicken and which is the egg? Could the complement of SK channel subtypes be the sole (or main) factor that leads to motoneuron subtypes? When during development do the SK channels appear – before or after muscle innervation? Answers to these questions will significantly further our understanding of neuromuscular development. We conclude that while there is clearly more to be discovered about C-boutons and some important questions remain, this synapse may provide a window through which we can further understand motoneuronal subtype development. This is an important question not only for physiologists, but also for those studying disease mechanisms, given that the most susceptible motoneurons in motoneuron diseases such as amyotrophic lateral sclerosis are fast motoneurons. In addition, there are changes to motoneuron fast–slow properties following injury or in response to exercise that are not yet understood. The work by Deardorff et al. could certainly help to further our understanding of “the speed match between motoneurons and muscle units” (Bakels and Kernell, 1993).

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)0,000
score de la tête « metaresearch » (Gemma)0,001
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: aucune
GenreSignal candidat: Commentaire · Signal consensuel: aucune
Score de désaccord entre enseignants0,009
Score d'incertitude au seuil0,029

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,001
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,000
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,002
Communication savante0,0020,004
Science ouverte0,0010,001
Intégrité de la recherche0,0020,002
Charge utile insuffisante (le modèle a refusé de juger)0,0090,002

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 Opus0,058
Tête enseignante GPT0,292
Écart entre enseignants0,234 · 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

Citations5
Publié2013
Routes d'admission1
Résumé présentoui

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