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. Author manuscript; available in PMC: 2023 Mar 28.
Published in final edited form as: Curr Biol. 2022 Feb 10;32(6):1439–1445.e3. doi: 10.1016/j.cub.2022.01.064

Blue light responses in Cancer borealis stomatogastric ganglion neurons

Sonal Kedia 1, Eve Marder 1,*
PMCID: PMC8967796  NIHMSID: NIHMS1775868  PMID: 35148862

Summary

In many animals, the daily cycling of light is a key environmental cue, encoded in part by specialized light-sensitive neurons without visual functions. We serendipitously discovered innate light-responsiveness while imaging the extensively studied stomatogastric ganglion (STG) of the crab, Cancer borealis. The STG houses a motor circuit that controls the rhythmic contractions of the foregut, and the system has facilitated deep understanding of circuit function and neuromodulation. We illuminated the crab STG in vitro with different wavelengths and amplitudes of light and found a dose-dependent increase in neuronal activity upon exposure to blue light (λ460–500nm). The response was elevated in the absence of neuromodulatory inputs to the STG. The pacemaker kernel which drives the network rhythm was responsive to light when synaptically isolated, and light shifted the threshold for slow wave and spike activity in the hyperpolarized direction, accounting for the increased activity patterns. Cryptochromes are evolutionarily conserved blue-light photoreceptors which are involved in circadian behaviors1. Their activation by light can lead to enhanced neuronal activity2. We identified cryptochrome sequences in the C. borealis transcriptome as potential mediators of this response and confirmed their expression in PD neurons which are part of the pacemaker kernel by single cell RNAseq analysis.

Keywords: cryptochrome, photosensitivity, crabs, pyloric rhythm

eTOC Blurb

Kedia and Marder report blue-light driven activity changes in neurons of a central pattern generating motor circuit. They characterize circuit and neuronal contributions to the light-driven response and its dynamics.

Results

The C. borealis STG is composed of 25–26 neurons that produce rhythmic contractions of the foregut3. These are organized into two central pattern generating circuits, of which the pyloric circuit controls the movements of the filtering apparatus, the pylorus. The pyloric rhythm is nearly constantly ‘on’ in the intact animal. Neurons of this circuit continue to produce similar rhythmic patterns for days even after the stomatogastric nervous system (STNS) is removed from the animal and placed in a dish. This system has been exploited for the detailed study of small neuronal networks for over 50 years4, 5. In a preparation this exhaustively studied we were surprised to find a novel feature, non-visual photoreception. This is a rare sensory response in motor neurons and an example of the distributed nature of light-sensing in neurons outside visual systems.

STG neurons are identifiable across animals and the pyloric network has a pacemaker kernel composed of a single oscillating anterior burster (AB) neuron, and two pyloric dilator (PD) neurons that serve to dilate the pylorus3. Inhibitory synapses connect these to a lateral pyloric (LP) and several pyloric (PY) neurons that constrict the pylorus. These neurons fire in tight co-ordination in a characteristic triphasic pattern to generate rhythmic pyloric contractions. Network oscillation frequencies vary across preparations, but these frequencies are relatively stable under fixed experimental conditions within a preparation6. The stable activity pattern of the pyloric rhythm in vitro allowed us to observe a marked increase in network activity in response to focused LED illumination.

Effect of blue light on different network states

We characterized the effects of blue light on network and neuronal activity. A 20x water immersion lens was used to focus LED illumination of a band of blue wavelengths (460–500nm, intensity 1.3mW/cm2) on the surface of the neuropil and somata of the STG neurons while recording activity intracellularly (Figure 1A). In intact networks, light increased network cycle frequency while the network maintained triphasic firing. The response returns to baseline levels when the light is turned off (Figure 1B, left panel). Two-thirds of all intact preparations tested had increased bursting activity in light (Figure 1G; quantified in Table S2, S3).

Figure 1. Response of pyloric circuit to blue light.

Figure 1.

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A. Schematic of experimental setup showing in vitro STNS preparation and light delivery via 20x water-immersion objective onto the surface of STG B. Characteristic triphasic pattern of activity in PD, LP and PY neurons recorded intracellularly (left panel). Middle panel shows activity of the same neurons in the presence of 1.3mW/cm2 light. Traces in the right panel show activity of the same neurons after the light was turned off. C. Schematic of decentralization process showing neuromodulatory inputs blocked pharmacologically along their axonal tract. D. Intracellular traces from PD, LP and PY neurons bursting sporadically after decentralization (left panel). Middle panel shows activity of the same neurons in the presence of 1.3mW/cm2 light. Traces in the right panel show activity of the same neurons after the light was turned off. E. Schematic of the pyloric circuit with glutamatergic inhibitory connections blocked with PTX to synaptically isolate the pacemaker kernel. F. Intracellular traces from PD, LP and PY neurons in PTX (left panel). PD neuron continues to burst. Corresponding cholinergic inhibitory post-synaptic potentials are seen in LP and PY neurons which do not burst. Middle panel shows activity of the same neurons in the presence of 1.3mW/cm2 light. Traces in the right panel show activity of the same neurons after the light was turned off. G. Burst frequency in light versus baseline in all three conditions shown in panels B, D and F. Each point represents values from one preparation in that condition. The solid blue line represents unity and the dashed line indicates a 10% increase. Preparations with negligible increase in burst frequency in light lie within the two lines. Every point outside the dashed line represents a preparation with increased burst frequency in light. H. Number of spikes per burst of PD neurons in intact, decentralized and PTX-treated preparations in the presence and absence of 1.3mW/cm2 blue light. Bar plots represent mean and standard deviation values. Individual points represent a single neuron. I. Duty cycle of PD neurons in intact, decentralized and PTX-treated preparations in the presence and absence of 1.3mW/cm2 blue light. J. Number of spikes per burst of LP neurons in intact and decentralized preparations in the presence and absence of 1.3mW/cm2 blue light. I. Duty cycle of LP neurons in intact and decentralized preparations in the presence and absence of 1.3mW/cm2 blue light. Paired t-tests between light and no light conditions. * =p<0.05, **=p<0.01, ***=p<0.001. See also Tables S1.

While STG activity is extremely stereotyped, there is a high degree of variability in the intrinsic neuronal components and neuromodulatory states across animals that can manifest themselves as differences in circuit responses to environmental changes. The STG receives descending inputs from the esophageal and commissural ganglia that maintain the rhythmic output of the STG via a wide range of neuromodulators7–11. To assess whether neuromodulation is necessary for the network response to blue light, we inhibited impulses in the neuromodulatory inputs to the STG pharmacologically (decentralization) (Figure 1C). In decentralized preparations rhythmic burst activity can slow down, become sporadic or stop completely6, 7. Light led to increased burst frequency in decentralized preparations with regular bursting and initiated bursting in sporadically bursting (Figure 1D) or non-bursting preparations (Figure 1G, quantified in tables S2, S3), suggesting that the response to light is not driven by neuromodulation. In fact, decentralization uncovered light-sensitivity in 4 out of 5 preparations that were insensitive to light in intact conditions (% increase in burst frequency in 1.3mW/cm2 light when intact:0.6±2.5, after decentralization:38.3±7.8, N=4) (Figure 1G). Because decentralization reduces burst frequency, the absence of measurable responses to light in some intact preparations can, in part, be attributed to ceiling effects when initial bursting activity is high.

We tested the contributions of circuit interactions versus cell-intrinsic factors to light-driven increases in bursting. Network oscillations in the pyloric circuit are initiated by the pacemaker kernel composed of AB and PD neurons. The pacemaker neurons continue to burst when isolated from their inhibitory synaptic inputs from LP and PY neurons pharmacologically, while LP and PY fire tonically and receive rhythmic inhibition from PD cholinergic synapses. We further treated decentralized preparations with picrotoxin to block glutamatergic synapses12 and measured the response of the isolated pacemaker to light (Figure 1E). Light increased PD burst frequency in the presence of PTX across preparations, implying that the pacemaker is equipped with light-sensitive machinery and is capable of driving circuit-level responses (Figures 1F, G; quantified in Table S2, S3).

Many activity changes accompanied the increases in burst frequency in response to light in all network states. PD neurons underwent small but significant membrane depolarizations in all conditions in light along with increases in number of spikes/burst and duty cycle (duration of activity of one neuron divided by the cycle period); and larger amplitude slow wave oscillations in intact and decentralized conditions (Figures 1H, I; Table S1). Synaptic connections may therefore contribute to slow wave changes in light in PD neurons, but changes in the other burst characteristics arise through intrinsic properties. The number of spikes per burst and duty cycle increased significantly in LP neurons in intact and decentralized preparations (Figures 1J–K, Table S1). LP neurons’ responses may therefore derive from a combination of intrinsic and PD-driven changes in light.

As a control for wavelength specificity STGs were exposed to longer wavelengths (λ520–560nm) of light which did not increase the burst frequency in any of the previous three network states described above (burst frequency baseline: 0.95±0.29, burst frequency in green light, 1.1mW/cm2: 1.15±0.23; p=0.25 paired T-test, N=7). Electromagnetic radiation can generate heat, so the temperature was monitored in the light path and found to remain constant. Besides, the effects of elevated temperature on pyloric circuit activity are well-characterized13 and differ markedly from network responses to light.

Dose dependence of light response on light intensity and duration

We quantified frequency changes in a range of intensities of light to establish whether the response was graded with intensity or an all-or-none switch. We focused our attentions primarily on the PD neurons as reporters of the pacemaker kernel. Preparations were exposed to increasing intensities of light for periods of two minutes with a minimum of two minutes darkness between each light exposure and the largest increase in burst frequency was measured. PD neurons in all three conditions had graded increases to increasing intensities of light (Figures 2A, B, C).

Figure 2. Impact of light intensity and duration on PD neuron activity.

Figure 2.

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A. Sample intracellular traces of a single PD neuron in an intact preparation in increasing intensities of light. Each blue box represents the presence of blue light of a different intensity of light. B. Sample intracellular traces of a single PD neuron in a decentralized preparation in increasing intensities of light. C. Sample intracellular traces of a single PD neuron in a decentralized preparation, in PTX, in increasing intensities of light. D. Maximum normalized burst frequency in different light intensities in intact preparations. Each color represents one preparation. E. Maximum normalized burst frequency in different light intensities in decentralized preparations. F. Maximum normalized burst frequency in different light intensities in decentralized preparations in PTX. Dashed lines represent 10% increase in burst frequency. G. Sample traces (black) of intracellular PD neuron membrane voltage recordings in PTX. Overlaid burst and spike frequencies (red and dark blue axes respectively) observed during delivery of different durations of 0.4mW/cm2 blue light. Overlaid blue boxes represent light pulse delivery. H. Effect of increasing pulse width with fixed light intensity on burst frequency across preparations. Each color represents a single preparation. Vertical panels represent single light intensities and burst frequencies are plotted across increasing pulse widths for each intensity of light. I. Effect of increasing light intensity of a fixed pulse width on burst frequency. Same data as in panel H. See also Tables S2–6.

We compared population responses to the different intensities of light in the different network states. A greater proportion of preparations were responsive to light in decentralized preparations at all light intensities, shifting the sensitivity of preparations to lower intensities (Figures 2D, E, Tables S2, S3, S4). In the preparations that were further treated with PTX, there was no decrease in sensitivity to light, indicating that there is a negligible role played by the inhibitory inputs to the pacemaker in the magnitude of burst frequency changes in light (Figures 2E, F; Table S4) (Burst frequency increase in 1.3mW.cm2 light Decentralized = 66±35%, PTX= 60±17%, p=0.3 paired T-test, N=7). The variability in response to different light intensities across preparations likely have contributions from neuromodulatory, circuit-level and intrinsic features.

Because lower intensities of light produced smaller increases in burst frequency, we next examined if the length of exposure to different intensities affects the magnitude of the response. A minimum pulse length of ~500msec was required to consistently see a response. 1,5,10, and 50s long light pulses were presented to decentralized preparations in PTX to remove modulatory and circuit influences. 1s pulses were repeated at 5X 1 Hz (total light exposure 5s, 6 pulses) and 5s pulses were repeated at 2X 0.2 Hz (total light exposure of 10s, 3 pulses) respectively to determine if the response was cumulative. All pulse lengths were delivered at multiple light intensities that spanned from 0.2 to 1.3mW/cm2.

Repeating short pulses (1s) at 1s intervals led to an additive effect on spike and instantaneous burst frequency. A maximum burst frequency was reached within ~5s of longer pulses and no further increases were observed when pulses of 5s or longer were repeated. The frequency stayed stable for the duration of 10 and 50s long pulses (Figure 2G). The lack of accommodation is an interesting difference from the dynamics of most sensory receptors14, 15.

This pattern was consistent across preparations. At all intensities of light, 5s and longer pulses produced larger responses than 1s long pulses (Figure 2H). The dose-dependence of the pyloric cycle frequency increase on pulse duration approached saturation at 5s in most conditions and preparations. For a single pulse length, the maximum burst frequency was dose-dependent on the intensity of light (Figure 2I). Intensity thresholds for eliciting a response varied across preparations (from 0.2–0.4 mW/cm2) as did their sensitivities to subsequent increases in intensity of light. There did not appear to be a saturating intensity for the range of intensities we tested.

There was a significant interaction between pulse duration and intensity in a two-way repeated measures ANOVA (F(8,32)=13.97, p<0.001, N=5) for baseline and different pulse lengths at 3 light intensities (0.2, 0.4, 0.8 mW/cm2). The pulse duration produced a larger response at higher intensities of light than at lower (One-way ANOVAs for simple main effects for Figures 2H, I in Tables S5, S6). Thus, the interaction between dose-response to intensity and length of light exposure is more complicated than a response to total power of radiant energy and is suggestive of interesting temporal dynamics in the underlying processes.

Intrinsic changes in PD neurons in light

Action potential and slow wave oscillation thresholds were measured in individual PD neurons to identify the physiological change underlying the light-evoked changes in network activity. Neurons were injected with current ramps from −2nA to 4nA over the course of one minute in the presence and absence of blue light in decentralized conditions with and without the addition of PTX (Figures 3A, B). In both cases, both spikes and slow wave oscillations occurred at lower membrane potentials in light (Figures 3C, D). The input resistance did not change significantly in light (data not shown). A change in intrinsic excitability of PD neurons therefore underlies some of the complex changes in pyloric network activity in light, especially in conjunction with the small depolarization of membrane potential we observe in light.

Figure 3. Shift in spike and oscillation threshold in light.

Figure 3.

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A. Intracellular voltage traces of a single PD neuron in decentralized conditions injected with a current ramp. The top panel is the membrane potential in response to a current ramp in control conditions. The second panel is recording from the same neuron in response to current ramp injection in the presence of 0.8mW/cm2 blue light. The third panel is the trace in response to the same current ramp after the light was turned off. The arrows indicate spike thresholds. The bottom panel is the current ramp injected into the PD neuron B. Same as in A) but in the presence of PTX. C. Mean and standard deviation values of spike threshold potentials in decentralized (n=5) and PTX (n=5) conditions in no light and light. Each color represents a single preparation. D. Mean and standard deviation values of oscillation threshold potentials in decentralized (N=5) and PTX (N=4) conditions in absence and presence of light. Paired t-tests between light and no light conditions. * =p<0.05, **=p<0.01

Cryptochrome expression in the STG

Cryptochromes are blue-green photoreceptor molecules expressed across plants and animals. They can also directly increase neuronal output in response to light as a means of controlling circadian rhythms in animal brains1, 2, 16. We identified two putative partial cryptochrome genes (GenBank accession #: MZ293206, MZ293207) by running BLAST searches on the C. borealis transcriptome17 using the identified sequences from the fellow decapod, Homarus americanus (Gene IDs: 121875146, 121877411). We also identified a putative opsin sequence, opsins being the canonical photoreceptor proteins (GenBank accession# MZ293208). We referenced an existing dataset of single cell RNAseq data of STG neurons18 and found that both putative cryptochrome sequences are expressed in PD neurons and there are no detectable reads of the opsin sequence (Figure 4). The pathway leading from light-activation of cryptochrome to increased neuronal firing in Drosophila involves a change in the conductance of K+-channels mediated by the redox-sensor beta-subunit (hyperkinetic) in response to cryptochrome-driven ROS accumulation19–22. A sequence for the beta-2 subunit of voltage-gated K+-channels was also identified in C. borealis through BLAST searches. This subunit is expressed in PD neurons (GenBank accession # MZ293209) (Figure 4). Hyperkinetic associates with both Shaker and ether a-go-go (EAG) classes of potassium channels23–25. We found that both Shaker and EAG sequences are expressed in PD neurons (Figure 4).

Figure 4. Single cell RNAseq expression of photoreceptor molecule sequences in PD neurons.

Figure 4.

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Box plots represent medians, first and third quartiles of counts of sequences in individual PD neurons. Each point corresponds to expression in a single PD neuron. Y-axis represents counts for RNA reads N=11

Discussion

Animals use light, or its absence, as an important signal to regulate their behavior. Canonically, light is sensed by neurons with photoreceptor pigments in dedicated visual structures for image formation, but many light-driven behaviors exist that are independent of visual systems26–30. In this paper we describe a response of a central pattern generating motor circuit to blue light. To the best of our knowledge, this is the only central pattern generating circuit with a strong and well-defined light-driven response. There are several reports of molluscs and arthropods with light-responsive neurons outside eyes31–34, but rarely have they been fully characterized with regards to the underlying conductances and their behavioral consequences35. It is certainly possible that some of these other light-responsive neurons constitute pathways that are important for the regulation of motor or circadian behaviors and merit further investigation.

The physiological responses of neurons in other species to light are mostly thought to be mediated by members of the opsin family33, 36. In contrast, in Drosophila, there is a cryptochrome-mediated blue-light response in specific neurons in the brain that is a critical component of circadian regulation and is the only reported instance of cryptochromes directly impacting neuronal activity2. The response we describe here might be a second instance of the cryptochrome-mediated neuronal activation.

The changes in the pyloric rhythm evoked by light are associated with changes in the spike and slow wave thresholds of PD neurons. Because the PD neurons are part of the pacemaker kernel for the pyloric rhythm, this suggests that the mechanism underlying the altered activity of the pyloric rhythm can be accounted for by changes in PD neuron excitability, so that they become active at more hyperpolarized membrane potentials. Because of the strong electrical coupling between the PD and AB neurons, these changes could be a direct action on the PD neurons, the AB neuron, or both together.

Although the STG is found beneath a hard carapace, it is close to the dorsal surface of the animal and strong illumination could reach the STG under certain environmental conditions. Blue-light is less absorbed by the ocean water than all other wavelengths and is therefore most likely to be a relevant environmental cue26. Perhaps surprisingly, cryptochrome is implicated in coordinating mass spawning events in response to moonlight in the coral Acropora, suggesting that even at low ambient light levels, these molecules can be behaviorally relevant37.

The pyloric network produces a feeding motor pattern and there is no known link between the responses of the STG neurons to a circadian control in the crab, although feeding behaviors themselves show circadian patterns. The pyloric frequency varies with the day/night cycle, and this may be driven by the blue-light response and relate to times of feeding/digestion. Light-entrainable peripheral clocks are known to occur widely across various tissues and organs38–43. There are especially strong links between circadian and metabolic cycles and feeding and light cues can alter peripheral circadian clocks for effective metabolism44. A connection could be revealed by future investigations of interactions of pyloric and circadian rhythms in C. borealis.

C. borealis is found both intertidally and down to depths of several hundred meters45. Importantly, in the spring and summer, crabs move to shallower, warmer waters for molting and reproduction46–48. Highest light intensities co-occur with highest temperatures during summer months. The pyloric rhythm increases at elevated temperatures, and it is possible that these factors combine to deal with an increased metabolic load in summer months.

STAR Methods

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Sonal Kedia (sonalkedia@brandeis.edu)

Materials availability

This study did not generate new unique reagents

Data and code

  • Raw data have been deposited at Zenodo and are publicly available as of the date of publication. DOIs are listed in the key resources table and are publicly available as of the date of publication. New sequences have been deposited at NCBI and are publicly available as of the date of publication. Accession numbers are listed in the key resources table.

  • This paper does not report original code.

  • Any additional information required to reanalyze the data reported in this paper is available from the lead contact upon request.

Experimental model details

Adult male Jonah Crabs (Cancer borealis) were purchased from Commercial Lobster (Boston, MA) and held in artificial seawater at 10–13°C on a 12 hour light/12 hour dark cycle without food. Animals were anesthetized for 30 min on ice prior to dissection. Dissections were performed as previously described49 in saline solution (440 mM NaCl, 11 mM KCl, 26 mM MgCl2, 13 mM CaCl2, 11 mM Trizma base, 5 mM maleic acid, pH 7.45). In brief, the stomach was dissected from the animal. The intact stomatogastric nervous system (STNS) was isolated from the stomach, including: the two bilateral commissural ganglia, esophageal ganglion, and stomatogastric ganglion (STG), with connecting motor nerves. The STNS was pinned down in a Sylgard-coated petri dish (10 mL) and continuously superfused with chilled saline.

Method details

Electrophysiology

The STG was desheathed and intracellular recordings from somata were performed with 15–30 MΩ glass microelectrodes filled with internal solution (10 mM MgCl2, 400 mM potassium gluconate, 10 mM HEPES buffer, 15 mM NaSO4, 20 mM NaCl50). Intracellular signals were amplified with an Axoclamp 900A amplifier (Molecular Devices). Neuronal identity was established after impaling the somata with sharp electrodes based on spiking activity observed on their respective nerves. Extracellular nerve recordings were made by building wells around nerves using a mixture of Vaseline and mineral oil and placing stainless steel pin electrodes within the wells to monitor spiking activity. Extracellular nerve recordings were amplified using model 3500 extracellular amplifiers (A-M Systems). Data were acquired using a Digidata 1440 digitizer (Molecular Devices, San Jose, CA) and pClamp data acquisition software (Molecular Devices, San Jose, CA; version 10.5). Extracellular nerve recordings were amplified using model 3500 extracellular amplifiers (A-M Systems). Data were acquired using a Digidata 1440 digitizer (Axon Instruments) and pClamp data acquisition software (Axon Instruments, version 10.5). Removal of neuromodulatory inputs to the STG (decentralization), was performed by adding isotonic (750 mm) sucrose plus 0.1 μm TTX to a Vaseline well built around the stn. Removal of inhibitory synaptic inputs was achieved by using 10−5M picrotoxin superfused continuously over the network12. For current injection ramps, PD neurons were impaled with two electrodes, one of which was used for current injections and the second for reporting membrane potential.

Light stimulation

Neurons were visualized with a custom-built epifluorescence microscope equipped with a 20x water-immersion UV fluorescence objective (Olympus, UMPLFLN 20XW). CoolLED pE-300 was used to provide LED illumination delivered through Chroma Alexa-488 filter set (catalog # 49011) for blue light and Chroma mCherry filter set (catalog # 49008) for green light. Light was delivered through the water-immersion objective while focused on the surface of neuropil through a water column. The intensities of light delivered through the objective were measured with a power meter (Thor Labs, S302C). Light stimulation was controlled manually for minutes long exposures and automated through custom programs in Clampex for short stimulus steps. Temperature was carefully monitored throughout the experiments, including during light pulse delivery, and also measured within the illuminated water column while delivering the highest intensity of blue light and found to remain unchanged by light.

Electrophysiology analysis

Recordings were acquired using Clampex software (pClamp Suite by Molecular Devices, version 10.5) and analyzed with custom MATLAB scripts. Traces were low-pass filtered to detect slow wave membrane oscillations. Minimum membrane potentials were measured at the trough of the oscillation. Oscillation amplitudes were measured as the difference between the negative and positive peaks of the filtered waveform. High-pass filters were applied to identify action potentials. To calculate spike threshold, spike onset was defined as the voltage corresponding to the maximum curvature of the first derivative of the voltage (dV/dt), when dV/dt crossed the threshold value of 10 mV/ms. Oscillation threshold was identified as trough value of the first negative peak in the low-pass filtered trace.

Sequence identification and RNAseq expression

There is no well-curated reference genome for C. borealis therefore BLAST searches was run on the C.borealis transcriptome using bait sequences from other decapods Homarus americanus (American lobster) and Penaeus vannamei (Pacific white shrimp). Identified transcriptome contigs were used to generate curated GenBank sequences which were released to NCBI for individual ascension numbers. The C. borealis cryptochrome-1 partial sequence shares 70.87%, 69.8%, and 69.63% identity with Penaeus vannamei cryptochrome-1-like (Gene ID 113818442), Euphausia superba (Antarctic krill) cryptochrome-1 (GenBank: KX238951.1) and Penaeus monodon (giant tiger prawn) cryptochrome-1-like protein sequences (Gene ID 119587748) respectively. The C.borealis cryptochrome-2 sequence shares 92.73%, 89.27%, and 89.09% identity with Homarus americanus cryptochrome-2 (Gene ID 121877411); Penaeus monodon cryptochrome-1-like and Penaeus vannamei cryptochrome-1-like protein sequences respectively. C. borealis opsin sequence shares 80.33%, 76.37%, and 67.83% identity with Leptuca pugilator (sand fiddler crab) opsin (Gene ID 311739213), Penaeus monodon compound eye opsin BCRH1-like (Gene ID 1935918524), Euphausia superba opsin 4 protein sequences(Gene ID 1 1004170850), respectively.

Single cell RNAseq data was available from 11 individual PD neurons20. Briefly RNA extraction had been performed from single identified STG neurons following which cDNA libraries were made and the software package Kallisto (v0.43.1) was used for the quantification of RNA-seq abundances through the generation of pseudoalignments of paired-end fastq files to the C. borealis annotated nervous system transcriptome19. The counts plotted in Figure 4 are raw values from Kallisto counts, unnormalized.

Quantification and statistical analysis

SPSS was used to run statistical tests on data. One-way repeated measures ANOVAs were run to compare burst frequencies in baseline versus light conditions followed by pair-wise comparisons with paired T-tests with Bonferroni correction. Average values from ten consecutive bursts with highest inter-burst frequency in light were used to obtain all burst characteristic values in light for pulses longer than 1 minute. A repeated measures two-way ANOVA was used to examine the interaction between intensity of light and pulse length with one-way repeated measures ANOVA to test simple main effects of pulse length and light intensity separately. Paired T-tests were used to measure differences between blue and green light responses. Wilcoxon rank sum test was used to compare average normalized increases in burst frequency to a single intensity of light in different conditions. Ns represent individual STNS preparations from individual crabs. Statistical tests values of all one-way repeated measures ANOVAs and pairwise comparisons are reported in the supplementary tables.

Supplementary Material

2

KEY RESOURCES TABLE

REAGENT or RESOURCE SOURCE IDENTIFIER
Chemicals, Peptides, and Recombinant Proteins
Tetrodotoxin Alamone labs T-550
Deposited Data
Raw data This paper DOI: 10.5281/zenodo.5095836
Cancer borealis sequencing National Center for Biotechnology Information BioProject archive https://www.ncbi.nlm.nih.gov/bioproject/PRJNA524309
C.borealis Cryptochrome-1 sequence NCBI GenBank MZ293206
C.borealis Cryptochrome-2 sequence NCBI GenBank MZ293207
C.borealis opsin-like sequence NCBI GenBank MZ293208
C.borealis Beta-2 subunit of VGKC sequence NCBI GenBank MZ293209
Experimental Models: Organisms/Strains
Cancer borealis Commercial Lobster, Boston, MA n/a
Software and Algorithms
MATLAB Mathworks https://www.mathworks.com/products/matlab.html
pClamp 10.7 Molecular devices https://www.moleculardevices.com/products/axon-patch-clamp-system/acquisition-and-analysis-software/pclamp-software-suite#gref
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Highlights.

Cancer borealis stomatogastric ganglion (STG) neurons are responsive to blue light

The absence of neuromodulation enhances the network activity increase evoked by light

Intrinsic excitability of PD neurons increases in light

STG neurons express mRNA encoding putative cryptochrome sequences

Acknowledgements:

We thank Dr. David Schulz for help with the data in Figure 4. This work was supported by funding from grant National Institute of Health R35NS 097343.

Footnotes

Publisher's Disclaimer: This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.

Declaration of Interests

The authors declare no competing interests.

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