Thermal sensitivity analysis data utilizing Q10 scanning, Boltzmann slope factor and the change of molar heat capacity

As a further elaboration of the recently devised Q10 scanning analysis (“Exceptionally high thermal sensitivity of rattlesnake TRPA1 correlates with peak current amplitude” [1]), the interval between current data points at two temperatures was shortened and the resulting parameters representing thermal sensitivities such as peak Q10s and temperature points of major thermosensitivity events are presented for two TRPA1 orthologues from rattlesnakes and boas. In addition, the slope factors from Boltzmann fitting and the change of molar heat capacity of temperature-evoked currents were evaluated and compared as alternative ways of thermal sensitivity appraisal of TRPA1 orthologues.

Boltzmann slope factor Q10 scanning Molar heat capacity Thermal sensitivity Infrared TRPA1 a b s t r a c t As a further elaboration of the recently devised Q10 scanning analysis ("Exceptionally high thermal sensitivity of rattlesnake TRPA1 correlates with peak current amplitude" [1]), the interval between current data points at two temperatures was shortened and the resulting parameters representing thermal sensitivities such as peak Q10s and temperature points of major thermosensitivity events are presented for two TRPA1 orthologues from rattlesnakes and boas. In addition, the slope factors from Boltzmann fitting and the change of molar heat capacity of temperature-evoked currents were evaluated and compared as alternative ways of thermal sensitivity appraisal of TRPA1 orthologues.
& 2016 The Author. Published by Elsevier Inc. This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/).

How data was acquired
Electrophysiology on TRPA1-expressing frog oocytes (TEVC)

Data format Analyzed Experimental factors
Temperature elevation on TRPA1 cRNA injected oocytes

Experimental features
Recorded temperature-induced currents were processed by a variation of Q10 scanning or fitted to equations to acquire thermosensitivity-associated parameters. Data source location Suwon, South Korea Data accessibility Data are with this article

Value of the data
Temperature-dependent activation of ion channels is typically quantitated by thermal coefficient Q10.
For ion channels with fast change of Q10 over varying temperatures, Q10 scanning is useful and further optimized in the data set given here.
Q10 scanning is improved to provide higher sensitivity for detection of maximal Q10s and more precise temperature parameters such as the temperature points yielding Q10 trace deflection and the maximum Q10.
The Boltzmann slope factor and the change of molar heat capacity of TRPA1s presented here have not been examined elsewhere for the purpose of comparing thermal sensitivities of ion channels, and are found to reflect difference in thermal sensitivity among thermally sensitive ion channels.

Data
To properly appreciate the high thermal sensitivity of TRPA1s from infrared-sensing snakes such as rattlesnakes and boas [1] in comparison with Drosophila melanogaster TRPA1 [2,3], a new analysis for temperature coefficient Q10 (fold increase of current upon 10°C temperature shift) was recently devised and called "Q10 scanning" [1]. By reducing the noise level of the temperature-evoked current through Gaussian filtering and shortening the interval between the two temperatures of Q10 calculation, the Q10 scanning method was tuned for higher Q10 sensitivity and more precise estimation of temperature parameters as presented here (Fig. 1). As alternative ways of analyzing temperature sensitivity of TRPA1s, the thermally induced current traces were fitted to equations to acquire the Boltzmann slope factor (Fig. 2) and the molar heat capacity change (Fig. 3).

Experimental design, materials and methods
The temperature-evoked current traces were previously acquired [1] by conducting two-electrode voltage clamping [4,5] on Xenopus laevis oocytes expressing each TRPA1. The current traces were data-reduced by the factor of 10 through replacing 10 data points with their average value, filtered by the Gaussian low pass filter at 1 Hz, and further smoothened by averaging neighboring 50 data points in order to minimize the noise level. For each t1 temperature, Q10 was obtained by its definition (Q10 ¼ (I2/I1) 10/(t2 À t1) ) with the use of two current and temperature data points apart from each other by 20,100, and 200 data points corresponding to 0.1, 0.5, and 1 s or 0.05, 0.25, and 0.5°C, respectively. The calculated Q10s were plotted as function of temperature t1. The peak Q10 was computed by averaging 100 data points flanking the maximum Q10. The temperature where Q10 starts to increase or which produces the maximum Q10 was referred to as deflection temperature (Td) or peak temperature (Tp), respectively. Td and Tp were compared with the Arrhenius activation threshold temperature (Tth) [6]. Comparison of the peak Q10s between 5-s and 1-s intervals for rsTRPA1 (B) and bTRPA1 (C). The former interval was used in Ref. [1] without Gaussian filtering at 1 Hz. D and E, The new peak Q10s with 1-sec interval were plotted with the Arrhenius Q10 [1] and fitted to the following equation of "exponential rise to maximum" for rsTRPA1 (D) and bTRPA1 (E). y¼a(1 À e À bx ), a¼ 123,129.5 and b ¼0.0017 for rsTRPA1.  To obtain the Boltzmann slope factors, traces were fitted to the Boltzmann equation using Sig-maplot12.0. To acquire the change in molar heat capacity ΔC p , the temperature-evoked currents were transformed to traces of lnK by plotting ln I/(I max À I) as function of temperature, assuming for simple comparative analyses that I max (peak current amplitude) is obtained with open probability of 1. The steepest part of the ln K graph was fitted with Sigmaplot 12.0 to the equation of "lnK ¼ΔS°0/R-ΔC p [1 À T 0 /T þln(T 0 /T)]/R" as function of T (temperature in Kelvin) to inquire the change of the molar heat capacity [7].
Acknowledgments I would like to thank Dr. Hana Cho for insightful comments to this manuscript and introduction to the data analyses used in the paper. This work was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education