Electrical Oscillations of Isolated Brain Microtubules

BRENDA C. GUTIERREZ; HORACIO F. CANTIELLO; MARÍA DEL ROCÍO CANTERO

VIRTUAL

Congreso; Reunión Anual de Sociedades de Biociencias SAI SAIC SAFIS; 2020

SAIC SAI SAFIS

Microtubules (MTs) are important cytoskeletal structures engaged in a number of specific cellular activities, including vesicular traffic and motility, cell division, and information transfer within neuronal processes. MTs also are highly charged polyelectrolytes. Recent in vitro electrophysiological studies indicate that different brain MT structures, including two-dimensional (2D) sheets (MT sheets) and bundles, generate highly synchronous electrical oscillations (Cantero et al. Sci Rep, 2016 & 2018). Although taxol-stabilized isolated MTs are capable of amplifying electrical signals, no information is heretofore available as to whether isolated MTs also engage in electrical oscillations. Herein we tested the effect of voltage clamping on the electrical properties of non-taxol stabilized isolated brain MTs. Electrical oscillations were observed at holding potentials between ±200 mV. Mean oscillatory currents were linear with respect to holding potential, with a change in conductance from 59.6 ± 3.6 nS to 160.8 ± 7.6 nS (n = 3) after loose-patch correction. This average change in conductance was much higher than previously reported for more complex MT structures. The frequency domain spectral analysis also disclosed a richer oscillatory response as compared to that observed in voltage clamped MT sheets from the same preparation. This interesting finding is consistent with the possibility that more structured MT complexes (i.e. bundles, sheets) may render more coherent responses at given oscillatory frequencies and raise the hypothesis that combined MTs may tend to entrain and oscillate together. The electrical oscillatory behavior of isolated brain MTs is consistent with that of ?ionic-based? transistors whose activity is synchronized in higher MT structures. The ability of MTs to generate, propagate, and amplify electrical signals may have important implications in neuronal computational capabilities.