How to resolve microsecond current fluctuations in single ion channels: The power of beta distributions

Abstract

A main ingredient for the understanding of structure/ function correlates of ion channels is the quantitative description of single-channel gating and conductance. However, a wealth of information provided from fast current fluctuations beyond the temporal resolution of the recording system is often ignored, even though it is close to the time window accessible to molecular dynamics simulations. This kind of current fluctuations provide a special technical challenge, because individual opening/closing or blocking/ unblocking events cannot be resolved, and the resulting averaging over undetected events decreases the singlechannel current. Here, I briefly summarize the history of fastcurrent fluctuation analysis and focus on the so-called "beta distributions." This tool exploits characteristics of current fluctuation-induced excess noise on the current amplitude histograms to reconstruct the true single-channel current and kinetic parameters. A guideline for the analysis and recent applications demonstrate that a construction of theoretical beta distributions by Markov Model simulations offers maximum flexibility as compared to analytical solutions.

Site-specific ion occupation in the selectivity filter causes voltage-dependent gating in a viral K+ channel

“…Since O-M and O-F gating cannot be evaluated directly by dwell-time analysis or similar methods, we utilize extended beta distributions 44 . Fast gating events with rate constants even much higher than the cut-off frequency of the low-pass filter of the recording system cause increased open channel noise (Fig.…”

“…The fit by the model in Fig. 1d with extended beta distributions 44 is given in black or red. (f , g) Voltage dependence of the rate constants ( f ) k OM and ( g ) k MO of Kcv NTS wt (black), Kcv NTS S42T (red), Kcv NTS G77S (blue) and G77T (blue open symbols).…”

Single-channel recordings of RyR1 at microsecond resolution in CMOS-suspended membranes

“…To extrapolate to these shorter time scales, we performed the extended beta distribution analysis. In this approach, it is recognized that closing events that are attenuated by limited bandwidth appear as excess open channel noise (22). With the appropriate modeling assumptions, the gating dynamics can be inferred (Methods; SI Note 4: Extended Beta-Distribution Analysis).…”

“…Data analyses using hidden Markov model based analysis procedures (19,20) were used to analyze channel gating events. In addition, we employ extended beta-distribution analysis (21,22) of these high-bandwidth data to extrapolate the observed closed state flickering dynamics to timescales as short as 35 ns.…”

Effects of Venoms on Largeconductance Cationic Channels on the Inner Nuclear Membrane of Rat Cerebellum Purkinje Neurons

“…Для характеристики впливу компонентів неочищених природних отрут ми вимірювали такі параметри поодиноких каналів, як імовірність відкритого стану каналів (Р о ) та амплітуду струму (I), щоб визначити належність каналу до певного типу і отримати інформацію про можливі механізми взаємодії компонентів отрути із структурними одиницями каналу. Важливо відзначити, що виділяють явну амплітуду (або видиму) «apparent amplitude» та справжню амплітуду струму «true amplitude» поодинокого каналу [17]. Видима амплітуда струму -це різниця амп літуди струму між рівнями відкритих іонних каналів у ділянці реєстрації.…”