To understand how Class IV neurons respond to noxious thermal stimuli, we built a new system employing a 1462-nm infrared (IR) laser as a step-like and local heating device (Figure 1A). The IR laser has been applied for the precise control of temperature with high spatial and temporal resolution, such as the biophysical analyses of the temperature dependency of thermoTRP channels (Yao et al., 2009) and heat-shock-mediated expression of transgenes in targeted single cells by IR-laser irradiation through a microscope objective (Kamei et al., 2008).

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The maximum firing rate of the wild type, dTrpA1¹ mutant, and pain³ mutant (Columns A–F) and Quantification of timing of maximum excitation of Class IV neuron of each genotype (Columns H–J).

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We first examined the in vitro heating profiles of the IR laser: the kinetics of temperature changes, controllability of heating, and spatial distributions of heat around the laser focus. To measure the microenvironmental temperature, we exploited the temperature dependence of the electrical resistance of a glass microelectrode (Palmer and Williams, 1974; Shapiro et al., 2012; Yao et al., 2009). The temperature within a radius of approximately 50 μm from the laser focus rapidly increased from an ambient temperature (25°C) to target temperatures (30–50°C) within 100 ms, and stayed almost constant at the maximum temperature throughout the 1 s irradiation (Figure 1B and C). Moreover, the temperature maximum was directly proportional to the power output of the laser (Figure 1B). Compared to the perfusion protocol involving a preheated solution that is introduced into the recording chamber (Xiang et al., 2010) as well as the direct heating of the chamber (Liu et al., 2003), the IR-laser system allowed us to reproducibly deliver more spatially restricted, and more temporally controlled stimuli.

Next, we stimulated Class IV neurons by means of this system and measured the cellular physiological responses. For this purpose, we dissected third instar Drosophila larvae, prepared fillet preparations, and performed extracellular single-unit recordings. The foci of the IR-laser irradiation were targeted onto the proximal dendritic arbors (the path length of branches between the IR-laser foci and soma was no longer than 100 µm). IR-laser irradiation of more than 30-mW laser output power evoked high-frequency firings in Class IV neurons (Figure 1D and E: 30 mW, 40.6 ± 4.8 Hz; 40 mW, 83.9 ± 7.3 Hz; n = 9 cells). From our calibration of the IR laser, an irradiation of 1-mW raised the temperature by an increment of ~0.6°C in the focused region (inset of Figure 1B); thus, the estimated temperature was ~43°C for the 30-mW laser output power. This threshold temperature was close to that of previous experiments, where the jumps of the firing rate were detected at around 40°C with perfusion of the preheated solution into the recording chamber (Xiang et al., 2010). We were intrigued by the firing patterns in response to IR irradiation of 40-mW laser power, which typically contained pauses that followed high-frequency spikes (see 40-mW in Figure 1D); and we characterized the underlying mechanistic details as described later. Our control or 'wild-type' larvae in the electrophysiological experiments carried a transgene of a Ca²⁺ probe that was expressed selectively in Class IV neurons, unless described otherwise.

We investigated how the IR-laser irradiations evoked high-frequency firings in Class IV neurons by extracellular recording. We focused on the roles of two members of the TRPA channel family, dTrpA1 and Painless. Previous studies had shown that the activation of both of the two channels in the neurons was required to induce nocifensive escape behaviors (Babcock et al., 2011; Zhong et al., 2012), and that the expression of either of the channels was sufficient to elicit thermocurrents in cultured cell lines (Sokabe et al., 2008; Wang et al., 2013). Therefore, we expected that these molecules served as primary heat-activated cation channels in the neurons.

dTrpA1 mutant (dTrpA1¹ homozygotes) and pain mutant (pain³ homozygotes) exhibited normal basal firing in the neurons (data not shown), but showed significantly lower firing rates during the IR-laser irradiation (Figure 1E: [dTrpA1¹] 30 mW: 0.5 ± 0.3 Hz, 40 mW: 43.8 ± 7.9 Hz, n = 10 cells; [pain³] 30 mW: 10.0 ± 3.0 Hz, 40 mW: 54.6 ± 4.8 Hz, n = 7 cells). Interestingly, dTrpA1¹ mutants displayed significantly longer latency time between the onset of the IR irradiation and the increase in firing rate when compared to the wild-type or pain³ larvae (Figure 1F and G; Time to Max. Firing Rate in Figure 1G: [wild type] 45.0 ± 7.1 ms, [dTrpA1¹] 698 ± 89.5 ms; [pain³] 61.6 ± 16.4 ms, p < 5.7×10^-6, t-test with Bonferroni correction; our results of other allelic combinations are described in Figure 1—figure supplement 1). The temporal pattern of the wild-type firing was not a simple summation of the two TRPA mutants; thus, we infer that the two heat-activated channels should function in a coordinated manner. Our results also strongly suggested that the firing responses of the wild-type neurons reflected intrinsic neuronal activities, dependent on the heat-activated channels and were not induced by photo damage (see also Figure 1—figure supplement 2).

Although the occurrences of intracellular Ca²⁺ rises are often taken to be a hallmark of neural activity, it was not clear that the Ca²⁺ rises were faithfully indicative of the activation of Drosophila sensory neurons. We therefore decided to confirm the functional relationship between the Ca²⁺ rises and the neuronal firing responses. We first examined the dynamics of changes of cytoplasmic Ca²⁺ concentration during IR-laser irradiations. For this purpose, transgenic strains were generated that highly and specifically expressed an intramolecular FRET-based Ca²⁺ probe, TN-XXL (Mank et al., 2008), in Class IV neurons (see Methods and Figure 2—figure supplement 1 for details). Using ratiometric imaging, we measured the Ca²⁺ changes in the neurons in whole-mount larvae (Figure 2A–E) or fillet preparations (Figure 2F).

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A sample file of FRET imaging.

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When the soma was irradiated with the IR laser, a large increase in Ca²⁺ was observed over the entire dendritic tree, which we designated as dendritic Ca²⁺ transients or simply Ca²⁺ transients (Figure 2A,B and Video 1). The rise of the Ca²⁺ transients emerged simultaneously in both proximal and distal dendrites, and decayed exponentially. Dendritic Ca²⁺ transients were also visualized by using GCaMP5G (Akerboom et al., 2012) as an indicator (Video 2), but we used TN-XXL throughout this study for monitoring Ca²⁺ dynamics in both whole-mount larvae and fillet preparations, which allowed more robust quantitative analysis in the presence of perturbations along Z-axis motions by body wall muscles.

Video 1

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The Ca²⁺ transients occurred in all-or-none fashion upon IR-laser irradiations; suggesting that the magnitude of the thermal stimuli was converted into another value of information (e.g. dendritic membrane potential), and the value higher than a presumptive threshold evoked Ca²⁺ transients. The probabilities of the occurrence of Ca²⁺ transients were dependent on the output powers of the IR-laser, which arose abruptly at around 36 mW (Figure 2C), so this high occurrence is one advantage of irradiation to the soma. Furthermore, the probabilities were significantly lowered in the neurons of dTrpA1 or pain mutants (Figure 2—figure supplement 3A), indicating that Ca²⁺ transients also reflect normal neuronal activities that depend on the heat-activated channels. Irradiation to the dendritic arbor also evoked Ca²⁺ transients, although this required higher IR-laser power compared to the stimulation of the soma (Figure 2—figure supplement 2). Once a Class IV neuron elicited a transient, that neuron then responded more weakly to the repetitive IR-laser irradiations onto the same location in the cell (data not shown). In contrast to the sharp Ca²⁺ rises throughout dendrites upon IR irradiations to somata, Ca²⁺ fluctuations within the somata were relatively slow (Figure 2A; 'soma' and Figure 2—figure supplement 3B).

We next explored the molecular basis of the dendritic Ca²⁺ transient. Excitability of Class IV neurons was prerequisite for this Ca²⁺ transient, as shown by the fact that the occurrence of the transients was completely blocked by overexpression of the inward-rectifier potassium channel Kir2.1 (Figure 2D), which hyperpolarizes neurons and decreases their resting membrane potential (Hardie et al., 2001). This raised the possibility that the transient was caused by Ca²⁺ influx from extracellular space (see another possibility discussed in Figure 2—figure supplement 3 and its legend) and that some of the voltage-gated Ca²⁺ channels (VGCCs) were involved. To verify these possibilities, we screened genes encoding α subunits of VGCCs for those necessary for the occurrence of Ca²⁺ transients; specifically, we recorded and analyzed probabilities and amplitudes of the Ca²⁺ transients in various VGCC loss-of-function mutants. A dramatic phenotype was found in mutants of the L-type VGCC gene (Ca-α1D^X7/AR66 and Ca-α1D^X10/AR66)(Eberl et al., 1998); normal Ca²⁺ transients hardly occurred in those mutants (Figure 2D and E). A similar defect was observed in the wild type when a selective inhibitor of L-type VGCC, Nimodipine (Gielow et al., 1995; Grey and Burrell, 2010), was applied (Figure 2F). These results showed that L-type VGCC-mediated excitability is required for the occurrence of Ca²⁺ transients in Class IV neurons (see our negative results of other types of the Drosophila VGCC family in 'Materials and methods').

As for mammalian neurons, it has been well known that there is a link between changes in Ca²⁺ levels, which are regulated by L-type VGCC, and cell-specific gene expression (Greer and Greenberg, 2008). Therefore, the expression level of dTrpA1 and/or pain could have been lowered in the L-type VGCC mutants. To test this possibility, we performed real-time PCR to quantitate the mRNA levels of dTrpA1 and pain in neural tissues of Ca-α1D mutants, but found no significant differences between the Ca-α1D mutant and the wild type (data not shown).

The Ca²⁺ transient in Class IV neurons was reminiscent of that in rat neocortical pyramidal neurons, which are also detectable throughout the entire dendritic arbor (Schiller et al., 1995). The occurrence of this transient in the pyramidal neurons requires voltage-gated Na⁺ channels (VGSCs) that are distributed along dendritic branches. In our system, however, the addition of Tetrodotoxin (TTX) had no effect on the dendritic Ca²⁺ transients in Class IV neurons (Figure 2—figure supplement 3C and E), indicating that VGSCs are required neither for the occurrence of Ca²⁺ transients nor for the regenerative propagation of membrane potential along the dendritic branches.

To elucidate the relationship between Ca²⁺ transients and neuronal activities, we performed extracellular single-unit recording and the ratiometric Ca²⁺ imaging simultaneously (Figure 3A). Throughout our simultaneous recordings in this study, the IR stimulation was given to the proximal dendrite. Under 40-mW IR-laser irradiation, peak amplitudes of Ca²⁺ transients did not display a strong correlation with maximum firing rates (Figure 3B; p > 0.46, ρ = 0.17, Spearman’s rank correlation test; n = 20 cells). In our analyses, the firing rates were computed by sliding a rectangular window function along the spike train with Δt = 400 ms (see 'Materials' and methods for details). Even when we increased the width of the sliding window (Δt) from 10 to 1000 ms in steps of 10 ms, there were no statistically significant correlations between the estimated maximum firing rates and the peak amplitudes of Ca²⁺ transients (p ≥ 0.1; Figure 3—figure supplement 1A).

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Upon closer inspection of the firing patterns with Ca²⁺ transients, we noticed characteristic pauses in firing that followed the high-frequency spikes (Figure 3A). Thus, we defined these spikes as a pair of unconventional spikes (US) based on the interspike interval (Figure 3C), and designated the firing pattern composed of the pause and US tentatively as a 'burst and pause' pattern. When we sorted datasets of the firing patterns in a descending order of the peak amplitude of Ca²⁺ transients, the occurrence of US showed a high correlation with the peak amplitude (Figure 3D and E; p < 1.9×10^–8, ρ = 0.91; Spearman’s rank correlation test; n = 20 cells). We also performed a post hoc parameter fitting analysis on the basis of our finding that the occurrence of the US showed a high correlation with the peak amplitude of Ca²⁺ transients (Figure 3E; see also its legend). More importantly, in each dataset, the minimal interspike interval within the US was invariably shorter than that within non-US firings (Figure 3F; p < 5.2×10^–6; paired Student’s t-test; n = 13 cells), indicating that large excitatory currents existed just prior to the pause in firing (see also Figure 3—figure supplement 1).

To address how inhibition of L-type VGCC affects the firing rate and the occurrence of Ca²⁺ transients and US, we recorded Class IV neurons in the presence of Nimodipine. Ca²⁺ transients and US were hardly detected in the spike trains (Figure 3G,H, and J; [Control] 1.6 ± 0.32, [Nimodipine] 0 ± 0; p = 0.001, Wilcoxon’s rank-sum test; n = 20 cells [Control] and n = 11 cells [Nimodipine]); in contrast, the firing rate was not decreased compared to that of the control and showed its peak around 100 Hz (Figure 3I). In other words, firing patterns were modified as if the 'burst and pause' pattern had been replaced with conventional high-frequency spike trains, indicating that the L-type VGCC is essential for the generation of US. We also found that firing rates decreased for short periods following the pauses (data not shown); therefore, we assumed that an after-hyperpolarization current is generated during the pauses (see 'Discussion'). Collectively, our findings strongly suggest that dendritic Ca²⁺ transients we observed in response to heat produced by the IR laser are generated by accumulations of L-type VGCC-dependent Ca²⁺ spikes in Class IV neurons.

The ectopic expression of thermoTRP has been widely used as a tool to achieve conditional controls of neuronal activity in vivo by modulating the ambient temperature (Bernstein et al., 2012). This is probably also the case with the ectopic expression of the lowest-threshold isoform of dTrpA1, one of the thermoTRPs described above, in Class IV neurons. dTrpA1 encodes four distinct isoforms that display different temperature sensitivities (Zhong et al., 2012); among them, the dTrpA1-A isoform (Viswanath et al., 2003) (also designated as dTrpA1.K) (Hamada et al., 2008) has the lowest threshold (~29°C) and shows little desensitization by repetitive heat-activations (Pulver et al., 2009). Forced expression of dTrpA1-A in Class IV neurons allows larvae to respond to a 30°C heat probe and elicit the nocifensive rolling behavior (Babcock et al., 2011; Zhong et al., 2012), possibly by endowing the neurons with higher sensitivity to the moderate-temperature stimulus. Consistent with this speculation, our recordings demonstrated that TrpA1-A-expressing neurons (TrpA1-A⁺ neurons) evoke both Ca²⁺ transients and the unique firing pattern below 20 mW (Figure 3—figure supplement 2A), to which the wild-type neurons were insensitive (Figure 1D), and all of other results (Figure 3—figure supplement 2B–E) strengthened the possibility that the cellular responses of Class IV neurons to IR irradiation reflected the intrinsic membrane properties.

Are the spikes detected in somata by extracellular single-unit recordings faithfully propagated through their axons? This had to be verified because of concerns in previous studies. For example, when neuronal activities with Ca²⁺ spikes are recorded extracellularly, the intracellularly detected spikes sometimes disappear in the voltage traces of extracellular single-unit recordings of axons (Schonewille et al., 2006). Another instance shows that intracellularly detected spikes are not always propagated along the axon (Monsivais et al., 2005). To explore these possibilities, we performed extracellular single-unit recordings from both the soma of a Class IV neuron and the axon bundle, including its own axon, and analyzed the correspondence between the firing patterns from somata, which coincided with US, and those from axon bundles (Figure 3—figure supplement 3A). Spikes from a single axon bundle can include those of not only Class IV but also other sensory neurons. Nonetheless, our findings indicate that the spikes recorded extracellularly from Class IV soma propagate faithfully through its axon (Figure 3—figure supplement 3B–D, see also the legends).

We hypothesized that the unique firing patterns accompanied by Ca²⁺ influx should be output signals provoking the robust nocifensive rolling behavior. To verify this hypothesis, we conducted a series of physiological and behavioral assays of Ca-α1D mutant or knockdown larvae (Figure 4 and Figure 4—figure supplement 1). We first examined the physiological responses of Ca-α1D-knockdown Class IV neurons. Both the occurrence of the Ca²⁺ transient and that of the unique firing pattern were suppressed in the neurons (Figure 4A and B) without a dramatic decrease in firing rate (Figure 4—figure supplement 1), as was seen in the case of pharmacological blockade of L-type VGCC (Figure 3G–I). We also observed that the total US number was significantly decreased in Ca-α1D-knockdown neurons compared to controls (Figure 4C; [white RNAi ^GL00094] 1.55 ± 0.20 total US number, [Ca-α1D RNAi ^HMS00294] 1.00 ± 0.00; p = 0.0055; Wilcoxon’s rank-sum test).

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The distributions of nocifensive escape locomotion latency for wandering third-instar larvae of the wild-type and Ca-α1D mutant larvae (Columns A, B) and The distributions of control larvae and larvae with Class IV neuron-specific white or Ca-α1D knockdown (Column D–G).

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We then examined how Ca-α1D mutant larvae (Ca-α1D^X10/AR66) responded to the heat probe and found that they displayed a significantly delayed response (Figure 4E), almost identical to dTrpA1 mutants (Babcock et al., 2011; Neely et al., 2011) (our data not shown). However it was reported that synaptic transmission at the neuromuscular junction (NMJ) is impaired in the Ca-α1D mutant larvae due to abrogation of the Ca²⁺ influx in both muscles and motor neurons (Ren et al., 1998; Worrell and Levine, 2008), so it was difficult to attribute the behavioral defect entirely to the role of L-type VGCC in Class IV neurons. Therefore, we knocked down expression of L-type VGCC selectively in Class IV neurons as was previously done (Kanamori et al., 2013). The phenotypic defect of the knockdown larvae was less dramatic than that of the whole-body mutant; nonetheless, the knockdown larvae displayed significantly delayed response in the rolling behavior than the control larvae (Figure 4F). These data support our hypothesis that L-type VGCC-dependent unique firing patterns in Class IV neurons are necessary for the highly penetrant induction of the larval nocifensive rolling behavior.

To explore the possibility of causal connections between the 'burst and pause' firing pattern and the rolling behavior, we performed a series of optogenetic activation experiments (Figure 5). It has been shown that larvae expressing channelrhodopsin-2 (ChR2) in Class IV neurons mimic the rolling behavior when ChR2 is activated by continuous light exposure (Hwang et al., 2007). We have established our assay of the induced rolling by expressing a faster kinetic variant of ChR2, ChIEF in Class IV neurons (Mattis et al., 2012). To address whether ChIEF-dependent intermittent firing of Class IV neurons is sufficient to elicit the rolling behavior, whereas continuous firing is not, we tried to recapitulate the naturalistic 'burst and pause' firings in the background of a Class IV-specific Ca-α1D-knockdown by activating ChIEF using square pulses of light. On and off durations of light pulses were set to be comparable to 'burst' and 'pause' timings (100 ms and 100 ms, respectively; Figure 5A top).

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With these illumination parameters, either continuous or intermittent firing patterns were successfully evoked in the knockdown neurons of fillet preparations (top of Figure 5A). In live animals, Ca-α1D-knockdown larvae displayed rolling when the continuous firing pattern was evoked, and the rolling occurred more efficiently by the pulsatile optogenetic activation (Figure 5B; [Continuous] 65.3 ± 9.2%, n = 75, [Intermittent] 86.3 ± 5.9%, n = 95, mean ± 95% confidence interval based on Clopper-Pearson method; p = 0.0017, Fisher’s exact test). Although the probability of rolling was rather high in the continuous activation condition (see 'Discussion'), this result is, nevertheless, consistent with the idea that the intermittent firing pattern facilitates the rolling behavior. However, it should be stressed that the intermittent pattern produced under our optogenetic experiment was distinct from the pattern of the wild-type neuron upon noxious thermal stimulations according to two quantitative features. First, the maximum firing rate of the optogenetic pattern was 40~50 Hz (data not shown) and lower than that of wild-type neurons (~80 Hz; Figure 1E). Second, none of the spike trains generated in our optogenetic condition fully met the definition of US (Figure 3C). Therefore, we reconsidered our idea that the occurrence of the US is a reliable metric for the artificial firing pattern, and we searched for other metrics that would explain all of the results of our three experimental settings: the effect of Nimodipine application (Figure 3D and H), the Ca-α1D-knockdown phenotypes (Figure 4A), and the optogenetics (the top of Figure 5A).

We noticed that fluctuations of firing rate were prominent around the time when each US occurred (the recording trace of Δ Firing rate of Figure 3A; see also Figure 3D). To express such fluctuations quantitatively, we first speculated that the number of the peaks of the firing rate during IR stimuli might be an appropriate metric and computed the firing rate by using the Gaussian kernel method (Figure 3—figure supplement 1C; see also below). Although we defined the peak of the firing rate using different parameter sets, we did not find statistically significant differences in the peak number between the controls and the samples in the above three experimental settings (data not shown).

Next, we focused our attention on the local steepness of the firing rate fluctuation during heat stimulation because a precipitous change in the firing rate is one essential component of burst firing. To quantify 'up' and 'down' of the firing rate fluctuation, we calculated the time derivative of the firing rate fluctuation during IR irradiation, defined peaks of firing rate fluctuation, and scored the total number of the peaks ('total peak number') as follows: first, the firing rate estimation was computed by using the Gaussian kernel method (σ = 25 ms); second, a threshold was configured as 0.5 of the primal peak value; finally, peaks of the time derivative above the threshold were specified (red circles in the bottom graphs of Figure 3A,G and 5A). With this analysis, the 'total peak number' showed a significant correlation with the total US number in control neurons (p = 3.17 x 10^–5, ρ = 0.79; Spearman’s rank correlation test; n = 20 cells; Figure 3K). We then showed a significant decrease in the total peak number in Nimodipine-applied neurons (Figure 3L; [Control] 2.00 ± 0.21 total peak number, [Nimodipine] 1.09 ± 0.091; p = 0.0034; Wilcoxon’s rank-sum test). Furthermore, the total peak number was significantly decreased in Ca-α1D-knockdown neurons compared to controls (Figure 4D; [white RNAi ^GL00094] 1.55 ± 0.20 total peak number, [Ca-α1D RNAi ^HMS00294] 1.00 ± 0.00; p = 0.027). As is intuitively obvious in the optogenetics experiment, the total peak number under the continuous activation was significantly different from that of the intermittent one (Figure 5C; [Continuous] 1.11 ± 0.11, [Intermittent] 5.00 ± 0.00; p = 4.11 x 10^-5).

To conclude, we consider the 'total peak number' is a reliable metric that can represent the complex burst and pause patterns and designate the peak of the time derivative of firing rate fluctuation as the peak of firing rate fluctuation for short. These results suggest that the total number of peaks of firing rate fluctuation in Class IV neurons plays a key role in increasing the likelihood of rolling locomotion upon noxious heat input. We designate this hypothesis as the 'burst number-coding' model because the burst (i.e., high-frequency firing) is accompanied by the peak of firing rate fluctuation.

To explore another potential impact of the 'burst and pause' firing pattern on escape behaviors, we tested whether it plays an important role in evoking the 'fast crawling' after noxious heat stimulation (Ohyama et al. 2013; 2015). To evaluate a causal link between the firing patterns and the fast crawling, we performed a set of optogenetic experiments as follows: First, we confirmed that ChIEF-expressing Class IV neurons could be activated with lower-power blue light (0.056 mW/mm²; 470 nm) and displayed lower-frequency firings (10~20 Hz) with no 'burst and pause' pattern in Ca-α1D-knockdown larvae (data not shown). Then, we observed that such a firing pattern triggered the fast crawling, even when no rolling behavior was evoked (Maximum speed of crawling stride: [before activation] 6.37 ± 0.29 mm/s, [after activation] 10.51 ± 0.66 mm/s, mean ± s.e.m., n = 24 larvae; p = 0.0269, Wilcoxon signed-rank test; see 'Materials and methods' for details). These findings indicate that lower frequency firing is sufficient for eliciting the fast crawling, whereas the occurrence of 'burst and pause' firing pattern is not required.

Finally we addressed two questions that are relevant to the polymodality of Class IV neurons (Xiang et al., 2010). The first one was whether the L-type VGCC is also required for the avoidance of the short-wavelength light stimuli (the directional shift of locomotion), for which dTrpA1-dependent neural activity of Class IV neurons was essential. Ca-α1D-knockdown larvae avoided blue light, as did the control larvae, when they were illuminated (Figure 4G). This finding indicates that not only L-type VGCC is dispensable for the photo-avoidance behavior, but also the synaptic transmission at the NMJ is not severely affected under our Ca-α1D knockdown condition.

The second question was whether the wild-type Class IV evokes the 'burst and pause' firing pattern in response to the blue light as it did upon the noxious thermal stimuli. We illuminated larvae expressing TN-XXL in Class IV with short-wavelength light of four different intensities, and found the following (Figure 6): (1) The firing change and the Max firing rate increased with the light intensity, but the firing rate was 32.1 Hz even at the strongest intensity (182.3 mW/mm²; Figure 6A–D), which exceeds the level that larvae normally experience in natural environments. This firing rate was far smaller than that in response to the thermal stimuli (83.9 ± 7.3 Hz; Figure 1E). (2) 'US-like spikes' (compare its definition in the inset of Figure 6E with that of US in Figure 3C) were detected only under the strongest light condition (Figure 6E). (3) Ca²⁺ transients were not observed at a light intensity (146.7 mW/mm²; data not shown). These observations indicate that the wild-type Class IV did not generate L-type VGCC-dependent US in response to the blue light.

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Our results, together with previous studies, indicate that molecular mechanisms in Class IV underlying avoidance to two distinct stimuli only partially overlap. Furthermore we propose the 'burst number-coding' hypothesis that, in Class IV neurons, the number of burst firings is employed as the facilitating signal for the heat stimuli and they instruct target neuron(s) to execute one out of the two possible behavioral outputs: the rolling behavior rather than the photo-avoidance (Figure 6—figure supplement 1; see 'Discussion').

It is accepted that the phototransduction machinery exists in the dendrite of Class IV neurons (Xiang et al., 2010). However, previous protocols for delivering noxious thermal or mechanical stimuli did not allow us to address whether the dendrite possesses transduction machineries for those stimuli. Our IR laser irradiation-measurement device is a noninvasive system, which is applicable to whole-mount animals and able to induce a rapid and local rise in the ambient temperature, mimicking the noxious heat input. With the resolution of our experimental conditions, the IR irradiation had no apparent effect on the integrity of organelles and evoked physiological responses of Class IV neurons. With the help of this system, we showed that the thermotransduction machinery is present in the dendrite.

The hypothetical thermotransduction machinery includes dTrpA1 and Painless of the TRPA channel family, which are required for the stereotype avoidance behavior to noxious heat stimuli (Neely et al., 2011; Tracey et al., 2003). Class IV neurons in the dTrpA1 mutant displayed a much longer latency time prior to the increase in the firing rate compared to the wild type. On the other hand, the rising profile of the firing rate in the pain mutant was comparable to that of the wild type, but the rate reached only 65% of that of the wild-type neurons. Therefore the temporal pattern of the wild-type firing response was not a simple summation of those of the two TRPA mutants. If dTrpA1 and Painless are the unique cation channels for the conductance of the putative thermocurrent, the time course of the firing in painless mutants may represent that of dTrpA1 activation, and vice versa. If this inference is the case, our results can be interpreted in a way that dTrpA1 can become activated to some extent by itself and that it is prerequisite for Painless to be properly activated. A previous electrophysiological analysis of Painless showed that Painless is a noxious-heat activated, Ca²⁺-requiring, Ca²⁺-permeable channel (Sokabe et al., 2008). Therefore, we suppose that noxious heat stimulation activates dTrpA1 and causes local Ca²⁺ entry in the dendrite, followed by the robust increase in Ca²⁺ conductance of Painless, leading to large depolarization. This results in gating of L-type VGCC and generation of the Ca²⁺ transient, most likely by accumulated Ca²⁺ spikes, throughout the dendrites of Class IV neurons.

Although little is known about subcellular localization of dTrpA1 and Painless in Class IV neurons (Hwang et al., 2012), they may distribute along the entire dendritic arbors. Among the subunits presumably composing the functional VGCC in Drosophila, Straightjacket (Stj) of the α2δ family is expressed in da neurons and required for the heat avoidance (Neely et al., 2010). Thus, Stj may coexist with Ca-α1D in the dendrite. It remains to be elucidated how the burst is followed by the pause. We assumed that any of the Ca²⁺-activated K⁺ channels (K_Ca channels) and/or other channels might be engaged in generating the pause through production of an after-hyperpolarization current.

In general, specialized sense organs such as nociceptors have thresholds at or near noxious levels, and increase activity with stronger noxious stimuli (Perl, 2007). Likewise, the probability of the Ca²⁺ transient occurrence in Class IV neurons arose abruptly at around an IR-power that was estimated to raise the temperature close to 47°C, and the neuron increased the magnitude of the responses at the suprathreshold temperature. What would be the potential advantages for Class IV to set the threshold by employing Ca²⁺ spikes? One advantage would be the improvement of the signal-to-noise ratio of the thermosensation. The cellular threshold of the response to the noxious heat could become precipitous by multiplying a physical property of the high-threshold channel (dTrpA1) by the probability of the Ca²⁺ spike generation.

Another advantage would be to utilize the generation of Ca²⁺ spikes to winnow a heterogeneous modality in a selective manner. Our observations highlighted two features of the neuronal response to the different noxious stimuli: (1) the presence or the absence of multiple peaks of firing rate fluctuation and (2) the high or low absolute value of maximum firing rate. We hypothesize that the Ca²⁺ spike can be a key signal encoding a specific modality: the total number of peaks of firing rate fluctuation transmits the noxious heat input by way of Ca²⁺ spikes; in contrast, the continuous firing train at a lower rate encodes the noxious light sensation (e.g. see Figure 1E and 6D). This means that the thermal stimuli induce the high-threshold and larger generator currents (orange line; Figure 6—figure supplement 1 bottom), while blue light inputs evoke the low-threshold and smaller currents (blue line; Figure 6—figure supplement 1 bottom). We showed that the heat-induced unique firing patterns of Class IV were conducted along the axon, which projects to the putative central pattern generator(s) driving the thermal nocifensive responses. It has been shown that Channelrhodopsin2-mediated activation of Class IV provokes the thermal nocifensive behavior (Hwang et al., 2007) and the photo-avoidance (Xiang et al., 2010). We predict that inward currents would be larger in the former.

Our optogenetic activation experiment shows that the multiple peaks of firing rate fluctuation is not essential for the nocifensive escape locomotion (rolling), but enhances its occurrence rate. Therefore, we speculate that such unique firing rate fluctuation may be decoded as a facilitating signal of rolling (the 'burst number-coding' hypothesis). It has also been shown in olfactory behaviors of C. elegans that specific activity patterns may modulate the probability of action selection (Gordus et al., 2015). Recently, it has been reported that combining mechanosensory and nociceptive cues synergistically enhances the selection of rolling behavior in Drosophila larvae (Ohyama et al., 2015). Altogether, the likelihood of rolling locomotion upon noxious heat stimulation can be potentiated by the input(s) from other sensory modalities and multiple peaks of firing rate fluctuation. We also noticed that the probability of rolling was rather high in the continuous activation condition (66.0%; gray bar in Figure 5B). We assume that almost all of the Class IV neurons were activated under our optogenetic conditions, so that such a high behavioral reactivity was elicited. On the other hand, lower probabilities of rolling were detected in the initial periods of the heat probe assay of Ca-α1D knockdown larvae (~20%, <2 s; Ca-α1D RNAi in Figure 4F). This low reactivity can be explained by local heat-stimulation that may activate a small number of neurons (Robertson et al., 2013).

The neural circuits in the central nervous system must read out the activity of Class IV neurons and distinguish one firing pattern from another to decode the polymodal sensory input. How are the two types of firing patterns in response to the distinct noxious inputs decoded and transformed into differential escape behaviors? Previous studies have shown that the burst coding is a behaviorally relevant mechanism (Krahe and Gabbiani, 2004). For instance, the bursts in an ultrasound-sensitive acoustic sensory neuron of the field cricket Teleogryllus oceanicus code for a conspicuous increase in amplitude of an ultrasound stimulus (Sabourin and Pollack, 2009). It is well known that in the cerebellar cortex, climbing fiber inputs evoke characteristic complex spikes in Purkinje neurons, which induce the dendritic Ca²⁺ entry through Ca²⁺ spikes and a subsequent pause in the spike train (Davie et al., 2008; Kitamura and Häusser, 2011; Llinas and Sugimori, 1980; Mathews et al., 2012). The firing response of Purkinje neurons is remarkably similar to that of Class IV neurons in terms of the pattern and the underlying mechanism. It should be noted that the pause of firing in Purkinje neurons evokes the high-frequency firing response in the target neurons of the deep cerebellar nuclei via the post-inhibitory rebound (PIR) mechanism (De Zeeuw et al., 2011). Moreover, it has been proposed that the pauses of firings per se convey signals (the ‘pause coding’ theory, De Schutter and Steuber, 2009; Hong and Optican, 2008). Another circuit evoking the nocifensive light-avoidance behavior may receive direct excitatory inputs from Class IV neurons; this would be consistent with our hypothesis that the dual codes of the polymodal sensory information are decoded and segregated as distinctive command signals in the downstream circuit. Recently, the candidate synaptic partner(s) of Class IV neurons were identified through functional and anatomical assays (Vogelstein et al., 2014; Ohyama et al., 2015); thus, our hypothesis can be tested by investigating the neuronal responses of these candidate neurons to noxious thermal stimulations of Class IV neurons.

The following fly strains were generated and/or used: (1) The overall structure of our construct for expressing the FRET-based Ca²⁺ indicator TN-XXL (Mank et al., 2008) in Class IV neurons was as follows: The TN-XXL ORF was flanked by 1.9 kb pickpocket (ppk) promoter (Grueber et al., 2003) and a SV40 polyA signal sequence. Three copies of this cassette with intervening gypsy insulators (Ni et al., 2009) were subcloned into a pCasper4-derived plasmid that contains a PhiC 31 attB site (Groth et al., 2004). The resulting construct (3×[ppk-TN-XXL]) was integrated into either attP40 or attP2. (2) Mutants of thermoTRP genes were pain¹ and pain³ (Sakai et al., 2009; Tracey et al., 2003) from T Sakai, and dTrpA1¹(Kwon et al., 2008) and dTrpA1^ins(Hamada et al., 2008) from P. Garrity. (3) Mutants of the L-type VGCC α subunit gene were Ca-α1D^AR66 from C Duch, and Ca-α1D^X10 and Ca-α1D^X7 (Eberl et al., 1998) from Bloomington Stock Center. (4) A mutant of the T-type VGCC α subunit gene was Ca-α1T^del (Ryglewski et al., 2012) from Bloomington Stock Center. (5) Mutants of the P/Q-type VGCC α subunit gene were cacophony^S (cac^S[Smith et al., 1998]) from RW Ordway and cac^ts4(Rieckhof et al., 2003) from JT Littleton. We examined the peak amplitude of thermo-dependent Ca²⁺ transients in the above T-type and P/Q-type VGCC mutants, and found that there was no statistically significant difference in the amplitude (data not shown). (6) Stocks related to CICR component genes were TRiP^JF03381 (dsRNA of Rya-r44F) from Bloomington Stock Center, and Itp-r83A^90B.0 and Itp-r83A⁰⁵⁶¹⁶(Venkatesh and Hasan, 1997) from Bloomington Stock Center. (7) Other transgenic lines were UAS-dTrpA1.K (attP2), UAS-Ca-α1D RNAi ^JF01848, UAS-Ca-α1D RNAi ^HMS00294, UAS-white RNAi ^GL00094, UAS-Lifeact:GFP, UAS-mito:HA:GFP, UAS-Kir2.1, UAS-GCaMP5G, GMR-Hid and UAS-Dcr-2 from Bloomington Stock Center, and UAS-ChIEF-tdTomato^C3-3(Wang et al., 2011) from Z Wang.

Exact genotypes of individual animals used in figures are described below:

Figure 1

(D) 3×[ppk-TN-XXL] (attP2)/ 3×[ppk-TN-XXL] (attP2)

(E-G)3×[ppk-TN-XXL] (attP2)/ 3×[ppk-TN-XXL] (attP2) (WT)

3×[ppk-TN-XXL] (attP40)/+; dTrpA1¹/ dTrpA1¹

pain³/pain³; 3×[ppk-TN-XXL] (attP2)/+

Figure 2

(A–C,F) 3×[ppk-TN-XXL] (attP40)/+

(D) 3×[ppk-TN-XXL] (attP40)/+ (WT)

3×[ppk-TN-XXL] (attP40)/+; ppk-Gal4/UAS-Kir2.1

Ca-α1D^X10/AR66; 3×[ppk-TN-XXL] (attP2)/+

Ca-α1D^X7/AR66; 3×[ppk-TN-XXL] (attP2)/+

(E) Ca-α1D^X10/AR66; 3×[ppk-TN-XXL] (attP2)/+

Figure 3

(A,B,D–J) 3×[ppk-TN-XXL] (attP2)/ 3×[ppk-TN-XXL] (attP2)

Figure 4

(A–D,F) w¹¹¹⁸/+; ppk-Gal4/+; 3×[ppk-TN-XXL] (attP2)/+ (Control)

ppk-Gal4/+; 3×[ppk-TN-XXL] (attP2)/UAS-white RNAi ^GL00094

ppk-Gal4/+; 3×[ppk-TN-XXL] (attP2)/UAS-Ca-α1D RNAi ^JF01848

ppk-Gal4/+; 3×[ppk-TN-XXL] (attP2)/UAS-Ca-α1D RNAi ^HMS00294

(E) w¹¹¹⁸/w¹¹¹⁸ or Y (WT)

Ca-α1D^X10/AR66

(G) ppk-Gal4/GMR-Hid; 3×[ppk-TN-XXL] (attP2)/+ (Control)

ppk-Gal4/GMR-Hid; 3×[ppk-TN-XXL] (attP2)/UAS-Ca-α1D RNAi ^JF01848

ppk-Gal4/GMR-Hid; 3×[ppk-TN-XXL] (attP2)/UAS-Ca-α1D RNAi ^HMS00294

Figure 5

(A–C) UAS-ChIEF-tdTomato^C3-3/UAS-Dcr-2; ppk-Gal4/ UAS-Ca-α1D RNAi ^HMS00294

Figure 6

(A–E) 3×[ppk-TN-XXL] (attP2)/ 3×[ppk-TN-XXL] (attP2)

To measure the temperature of microenvironment, we employed electrical resistance thermometry using a glass microelectrode (Palmer and Williams, 1974; Shapiro et al., 2012; Yao et al., 2009). To elucidate the relationship between the electrical resistance of an electrode and the temperature of the external saline solution (Xiang et al., 2010), we monitored the electrical resistances at various values of temperature of the solution. First, we heated the saline solution in a petridish up to 50°C with an inline heater (SF-28, Warner Instruments, Hamden, CT) that was regulated by a thermo-controller (TC-324B, Warner Instruments). Then, we turned off the heater and recorded the electrical resistances (R) of the electrode and the temperatures (T) of the solution simultaneously during natural cooling. The electrical resistances of glass microelectrodes were 5–10 MΩ at ambient temperature (~25°C). We measured the electrical resistances by giving square pulses (50 ms, 10 mV; 1 Hz) in the voltage clamp mode. The reciprocal of temperature (1/T) was plotted against the log of the electrical resistance (log R), so that the Arrhenius equations were estimated as a R-T transformation formula by linear regression.

Fillets were made from wandering third instar larvae with the cuticle facing down in the external saline solution (Xiang et al., 2010) (120 mM NaCl, 3 mM KCl,4 mM MgCl₂, 10 mM NaHCO₃, 10 mM trehalose, 10 mM glucose, 5 mM TES, 10 mM sucrose, 10 mM HEPES. pH adjusted to 7.25 with NaOH). To immobilize larvae, all of the segmental nerves were cut, and then central nervous systems were removed. Muscles covering the neurons of interest were gently digested by infusion of Protease Type XIV (0.5% w/v, Sigma-Aldrich, St. Louis, MO) through a glass micropipette (~1.2 MΩ) mounted on a PatchStar micromanipulator (Scientifica, East Sussex, UK). After the enzymatic treatment, a couple of perfusions of external saline solution were carried out to remove excess enzyme, hemocytes, and other cellular debris. No detectable difference in dendrite morphology of Class IV dendritic arborization neurons was observed before and after muscle digestion, indicating the neurons were intact.

Class IV neurons were identified by the fluorescence of TN-XXL driven by the ppk promoter (see details in Ca²⁺ imaging). Recording pipettes were pulled with a P-1000 puller (Sutter Instruments, Novato, CA) from thin wall borosilicate glass (B150-110-10, Sutter Instruments), filled with external saline solution, with a tip opening of 5 μm (800 kΩ–1MΩ). Gentle negative pressure was delivered to suction the soma to get good signal-to-noise ratios of recording traces. We mostly recorded activity of v’ada of Class IV neurons. Recordings were performed with a Multiclamp 700B amplifier (Molecular Devices, Sunnyvale, CA), and data were acquired with Digidata 1440A (Molecular Devices) and Clampex 10.0 software (Molecular Devices). Extracellular single-unit recordings of action potentials were obtained in current clamp mode, with an 8 kHz low-pass filter and sampled at 10 kHz or 20 kHz.

Data were analyzed by Clampfit 10.3.1.5 software (Molecular Devices) and custom programs written in MATLAB (MathWorks, Natick, MA). Extracellular spikes were detected by first band-pass filtering (the high-pass filter: RC monopole, f_c = 100 Hz; the low-pass filter: Butterworth 8-pole, f_c = 2 kHz) and then thresholding the extracellular voltage trace with the 'Threshold Search' plugin of Clampfit software. The Maximum firing rates were computed by sliding a rectangular window function along the spike train with Δt = 400 ms. The peaks of the time derivative of firing rate fluctuation were assigned as follows: first, the spike density estimation was computed by using the Gaussian kernel method (σ = 25 ms; Shimazaki and Shinomoto, 2010); second, the temporal differences of firing rate were calculated (time derivative of firing rate fluctuation; time interval = 0.1 ms); third, a threshold was configured as 0.5 of the primal peak value; finally, the peaks of the time derivative above the threshold were specified.

'Time to Max. Firing Rate' was defined as the left edge of the sliding rectangular time window that gave the earliest maximum firing rate in each spike train. To perform simultaneous recording from the soma and the axon bundle, we first obtained the extracellular recording from the soma, and then the cutting edge of the axon bundle in the same hemisegment was suctioned into the recording electrode with a resistance of 700–800 kΩ.

A 200-mW continuous wave oscillation IR-laser light source was connected to the microscope through the IR-LEGO-200 system (Kamei et al., 2008) (Sigma Koki, Tokyo, Japan) to provide IR-laser stimulation through a dry objective (40× UApo/340 NA 0.90, Olympus, Tokyo, Japan), and the IR-laser beam was focused onto the center of the field of view. The source of IR laser was a continuous wave semiconductor laser (SLD-1462-200-C; FiberLabs, Fujimino, Japan). Precise focus of the IR-laser was localized by the spotted heat evaporation of indelible marker ink (K-177N, Shachihata, Nagoya, Japan). All of the power values in the text and figures are settings of the laser driver. IR-laser power density was measured at the focal plane of the objective using a radiometric sensor head (UP17P-6S-H5-DO, Gentec-EO, Quebec, Canada) coupled with a power meter (UNO, Gentec-EO). The measured output power was ~48.2% of the preset power. Custom programs in Digidata 1440A controlled the duration and timing of IR-laser irradiation by opening a TTL-triggered shutter (Shutter Controller F77-6, Suruga Seiki, Shizuoka, Japan) in the IR-LEGO system.

A 100-W mercury light source (U-LH100HGAPO, Olympus) was connected to the microscope with a light guide to provide short-wave light stimulation through a filter (BP460-495, Olympus) and the objective, yielding an evenly illuminated light spot, which covered the entire Class IV dendritic arborization neuron. Light intensity was measured as in IR-laser irradiation. Custom programs in Digidata 1440A controlled the duration and timing of light illumination by opening a TTL-triggered shutter (SSH-R, Sigma Koki) in the light guide. To administrate 3 μM Tetrodotoxin (Nacalai, Kyoto, Japan) or 5 μM Nimodipine (Sigma-Aldrich), fillets were incubated in the chamber for 30 min before recording. 10 μM Thapsigargin (Nacalai) was employed to deplete the cytoplasmic Ca²⁺ store.

Ca²⁺ imaging of TN-XXL-expressing Class IV neurons was performed on fillet or whole-mount preparations. Fillet preparations were made essentially as in extracellular recording, except that the protease treatment was omitted when only Ca²⁺ dynamics were recorded. For whole-mount imaging, larvae were anesthetized with isoflurane and mounted in halocarbon oil on a microscope slide. Data were collected on an IX-71 (Olympus) equipped with an objective (40× UApo/340 NA 0.90, Olympus), Nipkow disk confocal system (CSU-X1, Yokogawa Electric, Tokyo, Japan) and two EMCCD imagers (iXon X3 DU897-BV, Andor Technology, Belfast, UK). The custom-made camera mount (Olympus) of each EMCCD imager was equipped to adjust either the rotation angle around the optical axis (for CFP imaging) or the displacements along X- and Y-axes (for YFP imaging). Using the adjustment devices, the two imagers’ fields of view were aligned with minimal distortion in the rotation angle and minimal displacements less than one pixel along the X- and Y-axes.

TN-XXL was excited with a 445-nm diode laser (CUBE 445-40C, Coherent, Santa Clara, CA). Images were acquired at 512×512 pixels or 256×256 pixels with 2x2 binning, in 14-bit dynamic range, and with 100 or 33 ms exposure time. CFP and YFP fluorescence signals were captured synchronously and separately by the two imagers with 10 or 30 Hz, through 490/40 and 578/105 band-pass filters (Semrock, Lake Forest, IL), respectively. In simultaneous acquisitions of extracellular single-unit recordings and Ca²⁺ imaging, two imagers were controlled by Solis 4.19 software (Andor Technology) and the exposure timings were recorded by Digidata 1440A; these timing data were used for the offline processing as synchronization cues. In the case of the Ca²⁺ image acquisition only, two imagers were controlled by iQ 1.10.3 software (Andor Technology). Data were analyzed by ImageJ (NIH) and custom programs written in MATLAB (MathWorks). The setting of regions of interest (ROI) was guided with the binary mask image generated by the dendritic morphology. The background signals were subtracted from CFP or YFP images; then the FRET ratios were calculated (see Figure 2—figure supplement 1). In response to IR stimulations, Ca²⁺ fluctuations with ΔR_peak larger than 10% were designated as Ca²⁺ transients.

The thermal nociception behavioral tests were performed essentially as described (Caldwell and Tracey, 2010; Hwang et al., 2007), with slight modifications. Animals were raised at 25°C in an incubator with 12 hr light/dark cycles and humidity was manually controlled (75–80%). Third instar larvae were gently picked up from the vial, washed twice with deionized water, and transferred to a 140×100-mm petridish with fresh 2% agarose. Excessive water was removed from the animals. For acclimation, animals were allowed to rest on the plate for at least 5 min before testing. The response latency was measured as the time interval from the point at which the larva was first contacted by the probe until it completed the first 360° roll.

The light nociception behavioral tests were performed essentially as described (Xiang et al., 2010), with slight modifications. Animals were raised and treated as in the thermal nociception test. The assay was carried out with a Macro Zoom Microscope system (MVX-10, Olympus). Light was delivered from a 100-W mercury lamp (U-LH100HGAPO, Olympus) through a MV PLAPO 1X objective (Olympus) at 2.5X magnification, yielding a light spot of 1.5 mm in diameter. Other devices we used were a shutter (SSH-R1X, Sigma Koki) in the light guide, a filter for the background light (30.5S-R64, Olympus), and a lens for a CCD camera (GE60, Library, Tokyo, Japan). A filter (GFP-3035D, Olympus) was placed into the above microscope to illuminate blue light (472.5 nm with 30 nm band width). The light intensity at 2.5X magnification was measured by a radiometric sensor head (UP17P-6S-H5-DO, Gentec-EO, Quebec, Canada) coupled with a power meter (UNO, Gentec-EO) and it was determined to be 0.72 mW/mm² in the light spot. Sixty-five to 104 animals were tested in each condition and the percentage of positive responses was calculated.

Larvae for optogenetic activation experiments, harboring the UAS-ChIEF-tdTomato transgene (Wang et al., 2011), were grown in the dark at 25°C for 4 days on fly food containing all trans-retinal (R2500; Sigma-Aldrich) at a final concentration of 0.5 mM. For behavioral experiments, one larva at a time was separated from food and placed into the center of a 9.5 x 13.5 cm square plastic dish filled with 2% agar (Bacto Agar; Becton Dickinson, Franclin Lakes, NJ). After 5 min of acclimation, the dish with larva was placed into the behavior rig. 5 cycles of 100 ms pulses followed by 100 ms pause intervals or a single 1 s long pulse of blue light (0.234 mW/mm²; Figure 5B), or a single 1 s long pulse (0.056 mW/mm² for the crawling assay below) were applied by using a collimated LED light source (M470L3-C1; ThorLabs, Newton, NJ) with an emission peak at around 470 nm. A data acquisition system (USB-6212 BNC; National Instruments, Austin, TX) provided the triggering TTL signals, with timing controlled by a custom LabVIEW program (National Instruments). We recorded videos of larval behavior by using a GE60 CCD image sensor (640 x 480 pixels; Library) at 30 frames per second. For the analyses of crawling stride speeds, larval locomotions were traced in videos by using 'Manual Tracking' Fiji plugin (ImageJ 1.46J, NIH, Bethesda, MD), and then the maximum stride speeds for 5 s before and after optogenetic activation were calculated. For electrophysiological recordings, 5 cycles of 100 ms pulses with 100 ms pause intervals or a single 1 s long pulse of blue light (0.294 mW/mm² for Figure 5A), or a single 1 s long pulse (0.056 mW/mm²) was applied from above through external saline solution. The Digidata 1440A digitizer (Molecular Devices) generated the triggering TTL signals, with timing controlled by a custom Clampex protocol (Molecular Devices).

RNA was purified from four larval CNS complexes for each genotype using an RNeasy kit (QIAGEN, Hilden, Germany). ReverTra Ace and Thunderbird (TOYOBO, Osaka, Japan) were used according to the manufacturers’ instructions. Sequences of the primers were: 5’-GCT TGT GCC CAG GGA GC-3’ and 5’-AGG ACA CAA TGT CCG GAT GAT CG-3’ (Probe 1), and 5’-GCG ACC AGA ATG GCG ACT TTA ATG-3’ and 5’-CCC GTA TCC ACT GGG ATG GAC-3’ (Probe 2) for dTrpA1; 5’-GCG ACA CCC AAG TTA TTA AGG GTC-3’ and 5’-GTT CAT CAA ACG TTG GCA GAT GC-3’ (Probe 1), and 5’-TGC TGA CAG GCG AGT TTG AC-3’ and 5’-GCC TGA GCC TTA ATA ACT TGG GTG-3’ (Probe 2) for pain; and 5’-GCT AAG CTG TCG CAC AAA TG-3’ and 5’-GTT CGA TCC GTA ACC GAT GT-3’ for rp49 used as a reference. Data were analyzed using the comparative C_T method on a StepOne Real-Time PCR System (Applied Biosystems, Foster City, CA).

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

The reagents, genomic datasets, and/or facilities were provided by the Drosophila Genetic Resource Center at Kyoto Institute of Technology, the Bloomington Stock Center, Vienna Drosophila Resource Center, the TRiP at Harvard Medical School (NIH/NIGMS R01-GM084947), the NIG stock center, the Developmental Studies Hybridoma Bank at the University of Iowa, the Drosophila Genomics Resource Center (DGRC), FlyBase, modENCODE, YN Jan, T Sakai, P Garrity, C Duch, RW Ordway, JT Littleton, S Ryglewski, Z Wang, T Suzuki, M Miura, T Kanamori, K Emoto, and S Yonehara. We also thank Y Xiang, N Tanaka, K Horikawa, T Ishihara, T Teramoto, S Takagi, M Suzuki, Y Kamei and Y Tanaka for advice on electrophysiology, IR-mediated heating and Ca²⁺ imaging; J Hejna for polishing the manuscript; and K Oki, J Mizukoshi, and M Futamata for their technical assistance. This work was supported by a grant from the programs Grants-in-Aid for Scientific Research on Innovative Areas 'Mesoscopic Neurocircuitry' (22115006 to T Uemura and 22115005 to MM), a grant from Takeda Science Foundation to T. Uemura, a Grant-in-Aid for Scientific Research (C) to T Usui (24500410), a grant from the programs Grants-in-Aid for Scientific Research on Innovative Areas 'Brain Environment' to T Usui (24111525), and the Platform Project for Supporting in Drug Discovery and Life Science Research (Platform for Dynamic Approaches to Living System) from the Ministry of Education, Culture, Sports, Science (MEXT) and Japan Agency for Medical Research and development (AMED). S-IT, DM and KO are recipients of a JSPS Research Fellowship for Young Scientists.

© 2016, Terada et al.

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