New insights into the structure and function of couplons.

It is widely accepted that the calcium transient in heart is a summation of many Ca2+ release events or sparks (Cheng et al. 1993). Each local release event is produced by a structure called a couplon (Stern et al. 1997), defined as ‘the functional grouping of RyRs and dihydropyridine receptors, (DHPRs; also known as L-type Ca channels) (and other junctional SR proteins) which may act in concert during EC coupling’ (Franzini-Armstrong et al. 1999). Calcium that enters the couplon through DHPRs triggers Ca2+ release from a cluster of RyRs (ryanodine receptors, sarcoplasmic reticulum Ca2+ release channels), thus producing a local release event. Each couplon obeys local control, which can explain, for example, the gradation of Ca2+ transients with trigger magnitude. The number of recruited couplons determines the transient amplitude. The number of DHPRs found in a couplon is of central importance, but is difficult to investigate experimentally. It seems certain that, at least in rabbits, multiple DHPRs must be present in each couplon because the probability of activation of local Ca2+ release events exceeds the probability that an individual DHPR will open during the action potential (Inoue & Bridge, 2003). In this issue of the The Journal of Physiology, Polakova et al. (2008) have produced a far reaching and insightful study that suggests that a rat couplon must contain a large number of DHPRs, perhaps as many as 40 on average. Their results show that DHPRs exhibit a low ‘coupling fidelity’ (the probability that a single DHPR opening will activate a local release event). Thus, the number of DHPRs present in the couplon must be large for the overall probability of local release to be high. It is instructive to consider how they arrived at this result and its implication for excitiation–contraction (E-C) coupling. The probability of couplon activation depends on the number of DHPRs physically present, the number of times each DHPR opens during an action potential or voltage clamp step, the current through each open DHPR, and the duration of each opening. From measurements of whole cell current and Ca2+ transients, however, it has been difficult to determine the individual contributions of these variables. Polakova et al. (2008) address this difficult issue with clever experimental manipulations and a sophisticated analysis. Rather than recording Ca2+ transients, they recorded Ca2+ spikes (Song et al. 1998), which allowed them to observe local release events. They also used a creative voltage-clamp protocol to alter some variables while keeping others fixed. For example, the principal approach was to briefly depolarize the cell to +60 mV, then abruptly repolarize it. This procedure forced calcium through the open channels and ensured a highly synchronized trigger. The resulting ‘tail current’ triggered spikes whose probability and latency distribution were measured. These authors mathematically expressed the theoretical spike probability with the following simple equation: (1) where Po is DHPR open probability, PCpl is coupling fidelity, no is number of sequential DHPR openings; and nDHPR is number of DHPRs present in a couplon. Polakovaet al. performed an analysis of tail currents and model-based curve fitting of the Ca2+ spikes and latency histograms to estimate the parameters of eqn (1), with the exception of Po, which they obtain from the literature. Several important findings emerged from their analysis. First, there are multiple re-openings of DHPRs. Secondly, the coupling fidelity is considerably less than 1 (roughly 0.15), even at negative tail potentials where the current through each open DHPR is quite large. Third, the parameter nPo, the number of open DHPRs at the end of a brief depolarizing step, is approximately 8. Accepting a value of Po between 0.2 and 0.3, the estimated nDHPR must be 20–40. This leads to the important conclusion that, if the coupling fidelity is low, a high probability of spike activation can only be maintained if a significant number of DHPRs open in parallel. Finally assuming 250 RyRs per couplon (Franzini-Armstrong et al. 1999), the estimate of nDHPR is consistent with the ratio of DHPRs to RyRs established by Bers & Stiffel (1993), which suggested an nDHPR of 35. These findings have important physiological implications. Anything that affects coupling fidelity can alter the probability that a couplon is recruited and hence a spark produced. Thus, prolongation of DHPR openings with β-adrenergic stimulation will, for example, increase coupling fidelity and the probability of local release events. From eqn (1) spike probability is steeply dependent on the number of DHPRs and the number of their sequential openings. If these are reduced in disease, then local release probability and the transient will be reduced. The authors established that reduced numbers of DHPRs and repeated DHPR openings both increase latency (and consequently its variance). Alterations in these can therefore significantly affect spike synchrony. This study clearly focuses one's attention on the parameters that should be measured to explain changes in synchrony and the magnitude of local release. These may occur in various pathological conditions, e.g. metabolic inhibition (Chantawansri et al. 2008) as well as in cells that function normally.