Frontiers in Synaptic Neuroscience (Mar 2019)
Optical Quantal Analysis Using Ca2+ Indicators: A Robust Method for Assessing Transmitter Release Probability at Excitatory Synapses by Imaging Single Glutamate Release Events
Abstract
Despite evidence that presynaptic efficacy and plasticity influence circuit function and behavior in vivo, studies of presynaptic function remain challenging owing to the difficulty of assessing transmitter release in intact tissue. Electrophysiological analyses of transmitter release are indirect and cannot readily resolve basic presynaptic parameters, most notably transmitter release probability (pr), at single synapses. These issues can be circumvented by optical quantal analysis, which uses the all-or-none optical detection of transmitter release in order to calculate pr. Over the past two decades, we and others have successfully demonstrated that Ca2+ indicators can be strategically implemented to perform optical quantal analysis at single glutamatergic synapses in ex vivo and in vitro preparations. We have found that high affinity Ca2+ indicators can reliably detect spine Ca2+ influx generated by single quanta of glutamate, thereby enabling precise calculation of pr at single synapses. Importantly, we have shown this method to be robust to changes in postsynaptic efficacy, and to be sensitive to activity-dependent presynaptic changes at central synapses following the induction of long-term potentiation (LTP) and long-term depression (LTD). In this report, we describe how to use Ca2+-sensitive dyes to perform optical quantal analysis at single synapses in hippocampal slice preparations. The general technique we describe here can be applied to other glutamatergic synapses and can be used with other reporters of glutamate release, including recently improved genetically encoded Ca2+ and glutamate sensors. With ongoing developments in imaging techniques and genetically encoded probes, optical quantal analysis is a promising strategy for assessing presynaptic function and plasticity in vivo.
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