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Hofgaard, J. P.

Publications and source records attributed to Hofgaard, J. P..

2 recordsLinked to original sources

Ephaptic coupling enables action potential conduction

BackgroundCardiac action potentials are believed to propagate solely by electrotonic transmission via gap junctions. In the alternative theory of ephaptic transmission, changes in extracellular electrical fields and ion concentrations may enable a cardiomyocyte to activate its neighbors. The involvement of ephaptic mechanisms remain highly disputed and has been discounted due to the reported inability of an isolated cardiomyocyte to activate another. MethodsIsolated rat cardiomyocytes were subjected to whole cell patch clamp. Transmission of action potentials was tested in current clamp in isolated cardiomyocytes pushed together and in native cardiomyocyte pairs. Sodium channel activation and inactivation was tested in voltage clamp. ResultsIsolated cardiomyocytes were pushed together end-to-end and one stimulated to fire an action potential. In 10 attempts, 2 pairs showed successful transmission of action potentials, showing that ephaptic transmission is possible. In native pairs, subthreshold depolarization was transferred between cardiomyocytes of native electrically coupled pairs, however, only after a delay, which is not be explained from electrotonic theory. Once action potentials were elicited in one cardiomyocyte of a native pair, the neighbor was activated with delays under 2 msec. The activation delay did not correlate with gap junctional coupling, again suggesting the presence of an alternative mechanism. In voltage clamp of native cardiomyocyte pairs, one cardiomyocyte was held at -90 mV while depolarizing pulses were applied to its neighbor. Consistently, activation of sodium channels in the depolarized cell led to activation of sodium channels in the hyperpolarized cell, which fits well with ephaptic but not electrotonic theory. Ephaptic transmission requires a shielded local domain. To separate this, we measured steady state inactivation in native pairs. As expected, all channels inactivated at -40 mV. However, when maintaining a potential of - 40 mV for an extended period, sodium current elicited at 0 mV re-emerged by de-inactivation. The de-inactivation at -40 mV support that a shielded domain exists where potassium currents can hyperpolarize the local potential. ConclusionsWe show for the first time that ephaptic transmission is possible, that it is most likely in operation, also in the presence of gap junctional coupling, and finally our study suggests that data obtained in single cells may fail to reproduce key features of the electrophysiology of cardiomyocytes that interact with neighboring cardiomyocytes.

physiology↗

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 unsupervised analyses.\n\nHere we describe and characterize an idealization algorithm based on Rissanens 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.

bioinformatics↗