254 research outputs found

    Evidence for non-independent gating of P2X(2) receptors expressed in Xenopus oocytes

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    BACKGROUND: P2X(2) receptor is an ATP-activated ion channel which is widely expressed in the nervous system, and mediates synaptic transmission. RESULTS: We recorded currents of P2X(2) receptors expressed in Xenopus oocytes from outside-out patches and have found that currents recorded from patches containing a single or multiple P2X(2) channels differ in a manner suggesting positive cooperativity. First, the currents from multichannel patches exhibit simultaneous transitions more frequently than predicted from the activity of independent channels. Second, the mean open lifetime at the current level of a single channel in a multichannel burst is about six times longer than the open time of currents from single channel patches, a trend opposite to what is expected of independent channels. These results indicate that the channels have positive cooperativity and that the longer opening is due to a slower closing rate. Third, from kinetic analysis the likelihood of the cooperative model is significantly larger than that of the independent model. Fourth, the open channel noise of currents from patches containing multiple channels is less than half that from a single channel, which is consistent with the channel properties being different when they are active in groups. CONCLUSION: Taken together, our results suggest that P2X(2) receptors are non-independent, but interact with positive cooperativity

    Unsupervised Idealization of Ion Channel Recordings by Minimum Description Length:Application to Human PIEZO1-Channels

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    Researchers can investigate the mechanistic and molecular basis of many physiological phenomena in cells by analyzing the fundamental properties of single ion channels. These analyses entail recording single channel currents and measuring current amplitudes and transition rates between conductance states. Since most electrophysiological recordings contain noise, the data analysis can proceed by idealizing the recordings to isolate the true currents from the noise. This de-noising can be accomplished with threshold crossing algorithms and Hidden Markov Models, but such procedures generally depend on inputs and supervision by the user, thus requiring some prior knowledge of underlying processes. Channels with unknown gating and/or functional sub-states and the presence in the recording of currents from uncorrelated background channels present substantial challenges to such analyses. Here we describe and characterize an idealization algorithm based on Rissanen's Minimum Description Length (MDL) Principle. This method uses minimal assumptions and idealizes ion channel recordings without requiring a detailed user input or a priori assumptions about channel conductance and kinetics. Furthermore, we demonstrate that correlation analysis of conductance steps can resolve properties of single ion channels in recordings contaminated by signals from multiple channels. We first validated our methods on simulated data defined with a range of different signal-to-noise levels, and then showed that our algorithm can recover channel currents and their substates from recordings with multiple channels, even under conditions of high noise. We then tested the MDL algorithm on real experimental data from human PIEZO1 channels and found that our method revealed the presence of substates with alternate conductances
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