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

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

Phosphatidylinositol-bisphosphate regulates intercellular coupling in cardiac myocytes

Changes in the lipid composition of cardiac myocytes have been reported during cardiac hypertrophy, cardiomyopathy, and infarction. Because a recent study indicates a relation between low phosphatidylinositol-bisphosphate (PIP(2)) levels and reduced intercellular coupling, we tested the hypothesis that agonist-induced changes in PIP(2) can result in a reduction of the functional coupling of cardiomyocytes and, consequently, in changes in conduction velocity. Intercellular coupling was measured by Lucifer Yellow dye transfer in cultured neonatal rat cardiomyocytes. Conduction velocity was measured in cardiomyocytes grown on microelectrode arrays. Intercellular coupling was reduced by angiotensin II (43.7±9.3%, N=11) and noradrenaline (58.0±10.7%, N=11). To test if reduced intercellular coupling after agonist stimulation was caused by PIP(2)-depletion, myocytes were stimulated by angiotensin II (57.3±5.7%, N=14) and then allowed to recover in medium with or without wortmannin (an inhibitor of PIP(2) synthesis). Intercellular coupling fully recovered in control medium (102.1±8.9%, N=10), whereas no recovery occurred in the presence of wortmannin (69.3±7.8%, N=12). Inhibition of PKC, calmodulin, or arachidonic acid production did not affect the response to either angiotensin II or noradrenaline. Furthermore, decreasing or increasing PIP(2) also decreased and increased intercellular coupling, respectively. This supports the role of PIP(2) in the regulation of intercellular coupling. In beating myocytes, conduction velocity was reduced by angiotensin II stimulation, and recovery after wash out was prevented by inhibition of PIP(2) production. Reductions in PIP(2) inhibit intercellular coupling in cardiomyocytes, and stimulation by physiologically relevant agonists reduces intercellular coupling by this mechanism. The reduction in intercellular coupling lowered conduction velocity