Figures and data
Attributes of pheromone-sensitive ORN spiking patterns.
Spikes were identified by their prominence in the raw ORN recording. The inter-spike interval (ISI) was defined as the time from one spike to the next. A train with ≥2 spikes with ISI ≤ 50 ms was considered a burst. The intra-burst interval was the ISIs within a burst, the inter-burst interval (IBI) the ISIs between two bursts, omitting any individual spikes in between. The inter-event interval (IEI) included the ISIs between bursts and individual spikes.
The conductance-based model of a simplified hawkmoth ORN.
(A) Schematic of the model containing a voltage gated sodium channel (Na+), a voltage gated potassium channel (K+), a low voltage activated calcium channel (LVA), a calcium and voltage activated potassium channel (BK), a leak channel, and a cAMP-gated leaky non-specific cation channel (Orco). The Orco channel is represented as a linear conductance whose value oscillates with a sinusoidal shape as a function of the ZT. The circadian rhythm in the Orco conductance is hypothesized to result from a cAMP-dependent increase in channel open-time probability (as found in Drosophila Orco: (Getahun et al., 2013)) via a circadian oscillation of antennal cAMP concentrations (Schendzielorz et al., 2015). This oscillation is driven by the circadian clock and serves as an input; the internal mechanism of the clock is not modeled explicitly. Arrows indicate the flow of ions through the channels. (B) Parametrized circadian oscillation in Orco conductivity, introduced as an external input to our model, representing the gating of Orco by cAMP whose concentration oscillates on a circadian timescale. The times of minimum and maximum cAMP concentration are indicated by colored arrows. (C) Parametrized IV curve of the Orco channel showing a linear behavior with the slope depending on the cAMP concentration. Line colors correspond to the arrows in panel B. (D) Markov-chain representing all possible states and transitions for each type of ion channel included in the model. The per capita transition rates (α and β) depend on membrane potential and in the case of the BK channel also on the intracellular Ca2+-concentration. The “N” state vectors contain the population of channels in each state “n”. Subscripts of “n” indicate how many activation and inactivation gates are in the open state. Directed edges are numbered in red. The only conducting state of each ion channel, representing the condition where all its gates are open, is shown in green. Panel A was drawn using pictures from Servier Medical Art. Servier Medical Art by Servier is licensed under a Creative Commons Attribution 3.0 Unported License.
Spontaneous activity of pheromone-sensitive olfactory receptor neurons (ORNs) of male M. sexta shows Orco-dependent circadian modulation.
(A) Example tip recordings of the spontaneous activity of one long trichoid sensillum during a period of high (top, average frequency ∼ 3 Hz) and low (bottom, average frequency ∼ 0.2 Hz) activity. (Bi) Spontaneous spike frequency of one long-term ORN recording during 17:7 light-dark cycles (same experiment as in A, colored arrows indicate respective zeitgeber times (ZT)), indicated by the black-white bar at the top, increased during each activity phase and was low during the resting phases. Spike frequencies were averaged for each 1 h bin. (Bii) Mean spontaneous ORN spike frequency across all LD animals in 1 h bins. Data from the individual in Bi is highlighted in red. Recordings had different lengths, therefore the number of recordings used for the element-wise mean for each 1 h bin decreased with the time since the start of the recording, indicated in the top panel. (Biii) Mean spontaneous ORN spike frequency across all LD animals in 1 h bins during the first 48 hours revealed circadian activity. (Ci) The spontaneous spike frequency of one long-term ORN recording in constant darkness (DD, the expected times of lights on are represented by grey bars above) exhibited a circadian pattern. The peak activity shifted in DD due to the animal’s endogenous, free-running circadian period τ = 21.27 h. (Cii) Mean spontaneous ORN spike frequency across all DD animals in 1 h bins. Data from the individual in Ci is highlighted in red. (Ciii) Mean spontaneous ORN spike frequency across all DD animals in 1 h bins during the first 48 hours after aligning the time to the first maximum in spontaneous activity (see Methods) revealed circadian activity. (Di) The spontaneous spike frequency of one long-term ORN recording in constant darkness with infusion of the Orco antagonist OLC15 (orange frame) dissipated the circadian rhythm of spontaneous activity. (Dii) Mean spontaneous ORN spike frequency across all OLC15 animals in 1 h bins. Data from the individual in Di is highlighted in red. In contrast to LD and DD conditions, the spike frequency decreases over time with prolonged exposure to OLC15. (Diii) Mean spontaneous ORN spike frequency across all OLC15 animals in 1 h bins (mean ± SD) during the first 48 hours after aligning the time to the first maximum in spontaneous activity (see Methods). In contrast to LD and DD conditions, the circadian change in spontaneous spiking frequency disappeared. (E) The slopes of the linear fits to the binned spiking activity of each individual animal in the three different conditions (see Methods). Each dot indicates the slope for one experiment. The line indicates the mean. The slope for OLC15 is significantly different from control LD.
Blocking Orco removed circadian modulation of spontaneous ORN spiking patterns.
Some attributes of the spontaneous ORN activity were significantly different (Wilcoxon signed-rank test, α = 0.05) between the time windows of low vs. high activity, mostly in LD (white boxes) and DD (gray boxes) conditions, but never when Orco was blocked with OLC15 (orange boxes). In both LD and DD, the mean spiking frequency was increased during high activity (Ai, Aii). Only in LD but not in DD, the mean inter-burst intervals (IBI; Bi, Bii), the relative number of spikes belonging to a burst (Ci, Cii) and the mean inter-event interval (IEI; Di, Dii) decreased significantly during the high activity period. Both in LD and DD the mean burst duration (Ei,Eii), mean number of spikes per bust (Fi,Fii), and mean intra-burst intervals (Gi, Gii) did not differ between low vs. high spiking activity. Also, with Orco blocking, the attributes for low vs. high activity did not differ for any of the attributes tested (Aiii-Giii). In DD and OLC15conditions, activity phases were aligned as described in the Methods; thus, low activity in DD was at subjective ZT 19 and in OLC15 at subjective ZT 13, high activity was in both cases at subjective ZT 24. ZTs for low and high activity in LD were 10 and 0, respectively.
Blocking Orco removed circadian regulation of ultradian rhythms in the spontaneous ORN spiking pattern.
Heat map of the instantaneous frequencies (1/ISI) over two consecutive days of long-term tip-recordings of one pheromone-sensitive long trichoid sensillum under different conditions (LD (A), DD (B), OLC15 (C)) in each panel. Pixel color indicates the counts of instantaneous frequencies in that respective bin. The points fall mostly in a band of high frequencies (>10 – ∼100 Hz) and low frequencies (0.01 – ∼10 Hz), with the high-frequency band representing the instantaneous frequencies of spikes within a burst and the low-frequency band the instantaneous frequency between bursts. (A, B) The high frequency band indicates daily and circadian modulation of frequency prevalence. In addition, the low frequency band (<0.01 Hz to ∼ 10 Hz) also displayed circadian modulation of the frequency composition. (C) Infusion of OLC15 deleted the circadian modulation in both frequency bands and enhanced the ultradian rhythm of frequency prevalence.
Blocking Orco affected ultradian and infradian frequencies in the spontaneous ORN firing patterns.
The Fourier analysis of spontaneous spiking activity revealed rhythms with ultradian (<20 h; dark grey), circadian (20-28 h; white), and infradian periods (>28 h; light grey) in LD (Ai), DD (Bi), and OLC15 (Ci). Each line represents one animal where each triangular marker is at the local maximum in the frequency spectra obtained for that animal. The histograms above illustrate how often specific periods of spiking activity rhythms occurred averaged over all animals. Circadian rhythms were detected in LD (N = 5 of 11), DD (N = 7 of 10), and OLC15 (N = 4 of 12). Wavelet analysis of LD (Aii), DD (Bii), and OLC15 (Cii) confirmed the occurrence of multiscale periods. Example plots for one animal each, the same animals as in Figure 5. For each panel, the top plot depicts the mean firing frequency, the middle plot the wavelet power in the same period range as panels i, and the bottom plot the wavelet power for infradian periods up to 7 h on a log scale to highlight infradian time scales.
Orco is not under control of the TTFL-based molecular circadian clock.
Relative expression levels of Orco mRNA from male hawkmoth antennae raised under LD conditions did not differ significantly (ANOVA on ranks, H(2) = 5.60, p = 0.061) between ZT 1 (end of activity phase), ZT 9 (resting phase), and ZT 17 (beginning of the activity phase). timeless mRNA levels from male hawkmoth antenna served as control and were published in Schneider et al. (2025).
The model adequately reproduces the firing pattern of the biological ORN.
(A) The model activity (bottom trace) displays both isolated spikes and bursts of variable length as in the original recording (top trace). The model represents an intracellular recording whereas the biological recordings were done with extracellular electrodes. (B) Semi-logarithmic plot of burst length distribution of an experimental LD recording (top) and simulated model (bottom) of spontaneous action potential activity of pheromone-sensitive neurons. Both the model and the recordings display exponential decrease of the count’s density as a function of the burst length, shown as a linear decrease in the logarithmic scale.
Comparison of the circadian modulation of model and ORN spiking attributes.
Mean spike frequency and percentage of spikes that belong to bursts show anti-phasic circadian oscillations both in the simulated model (left) and in the biological recording (right).
The model captures the Orco-dependent circadian modulation of ultradian spiking rhythms.
Heat map of the simulated model, pixel color indicates the density of instantaneous frequencies in that respective bin. The points can be roughly divided in a band of high frequencies (top, ∼50 –80 Hz) and low frequencies (bottom, ∼0.1 – 5 Hz), with the high-frequency band representing the instantaneous frequencies of spikes within a burst and the low-frequency band the instantaneous frequency between bursts. (A) Simulated spikes with circadian regulation by the Orco channel; the inter-burst frequencies varied widely with circadian rhythmicity while the frequencies within burst remained approximately constant. The simulated results also reproduced the “merging” effect between the two bands when the bottom one approaches the top one. (B) Simulated spikes without circadian regulation of Orco had no circadian oscillations.
Parameter values for model currents.
