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A dedicate sensorimotor circuit enables fine texture discrimination by active touch [1]

['Jie Yu', 'School Of Life Sciences', 'Idg Mcgovern Institute For Brain Research', 'Tsinghua University', 'Beijing', 'Tsinghua-Peking Center For Life Sciences', 'Xuan Guo', 'Shen Zheng', 'Wei Zhang']

Date: 2023-01

Active touch facilitates environments exploration by voluntary, self-generated movements. However, the neural mechanisms underlying sensorimotor control for active touch are poorly understood. During foraging and feeding, Drosophila gather information on the properties of food (texture, hardness, taste) by constant probing with their proboscis. Here we identify a group of neurons (sd-L neurons) on the fly labellum that are mechanosensitive to labellum displacement and synapse onto the sugar-sensing neurons via axo-axonal synapses to induce preference to harder food. These neurons also feed onto the motor circuits that control proboscis extension and labellum spreading to provide on-line sensory feedback critical for controlling the probing processes, thus facilitating ingestion of less liquified food. Intriguingly, this preference was eliminated in mated female flies, reflecting an elevated need for softer food. Our results propose a sensorimotor circuit composed of mechanosensory, gustatory and motor neurons that enables the flies to select ripe yet not over-rotten food by active touch.

The physical property is essential for us to access the palatability of food. We tend to feed on food within certain range of hardness. The difficulty to masticate or swallow indicates that the food is unripe or not well-cooked. On the contrary, food that are too soft or viscous could be a sign of over-ripen or contamination of pathogenic microbes. The texture of food is sensed by the mechanosensors on the lips and tongues but the molecules and neurons mediate the sensation are largely unknown. In the current study, we report that fruit flies are most attracted to chewy food, rather than those with too low or too high stiffness. A group of mechanosensory neurons on the fly proboscis are activated during active probing on food surface and promote ingestion by activating the sweet-sensing neurons. These neurons also activate motor neurons to facilitate food ingestion. The texture preference is versatile as mated female flies switch their preference toward softer food.

Funding: This work was supported by grants from the Innovation 2030 Major Project of the Ministry of Science and Technology of China (2021ZD0203300) to W.Z. This work was supported by grants 31871059 and 32022029 from the National Natural Science Foundation of China, grant Z181100001518001 from the Beijing Municipal Science & Technology Commission, and a ‘Brain+X’ Seeds grant from the IDG/McGovern Institute for Brain Research at Tsinghua to W.Z. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.

In the current study, we report that fruit flies are most attracted to chewy food, rather than those with too low or too high stiffness. A group of mechanosensory neurons on the proboscis are activated during active probing by moderate stiffness and promote ingestion by activating the sugar-sensing neurons. These neurons also activate motor neurons to facilitate food ingestion. This preference is regulated by mating states and may aid flies the ability to avoid food that are too soft or watery so that they are away from overripe food or the risk of being stuck.

Besides the chemical and mechanical cues from food, female flies’ feeding behavior is also regulated by reproductive states. It was reported that a newly mated female fly was more attracted to food rich in yeast and polyamines [ 16 – 19 ]. Mated flies also exhibit a higher preference to acid and salt [ 20 , 21 ]. This post-mating switch of feeding preference is essential for the egg development [ 22 – 25 ]. However, whether the preference for food stiffness is also subjected to post-mating regulation is unknown.

In human, the physical properties of food are assessed by sensory neurons innervating the tongue, mouth cavity and pharynx [ 9 ]. However, the molecular and cellular mechanisms underlying this sensation are largely elusive. A line of studies using Drosophila have provided valuable insights into how the mechanical information during food engagement and ingestion is sensed and processed [ 10 – 12 ] and how it is integrated into the feeding control circuit to coordinate food intake [ 10 , 13 – 15 ]. The mechanosensory neurons underneath the taste sensilla are activated when the labellum contacts food substrate above certain stiffness range and this activation suppresses feeding by inhibiting the sugar-sensing gustatory neurons [ 10 ]. The labellum multi-dendritic neurons (md-L) that innervate majority of the sensilla employ dTmc to sense the hardness or viscosity of food so as to suppress feeding [ 11 ]. However, in most of these studies, flies were allowed to choose between soft (0.25~0.5%, measured as agarose concentration) and hard (1~2%) food sources. While the soft end felled into the range of the food patches that flies were most likely to feed in the natural environment, the hard end was usually beyond the limit that was seen for optimal food sources [ 10 – 12 ]. Despite earlier attempts to establish the rough range of food hardness that the flies prefer, the most palatable stiffness range of food remains unclear and awaits further characterization.

The physical property is essential for animals to access the palatability of a food source [ 1 – 4 ]. Animals tend to feed on food within certain range of hardness. The difficulty to masticate or swallow indicates that the food is unripe or not well-cooked. On the contrary, food that are too soft or viscous could be a sign of over-ripen or contamination of pathogenic microbes [ 5 – 8 ]. Thus, together with chemical signals, the textural properties of food provide vital information of the ingestibility and digestibility before the food is ingested.

Animals generate voluntary movements of their sensory organs to explore the environment. For example, during food searching and chewing, specialized mechanosensory receptors on the hands and tongues gather information about the properties of food (texture, hardness, chewiness, etc.). Proprioceptive signals encoding joint movements and positions, arise from muscle engaged in chewing are also involved in this process. Simultaneous cutaneous and proprioceptive information from the food elicits haptic feedback to the brain in order to evaluate the physical property of the food.

Results

The TRP channel iav is essential for fine texture sensing Previous studies have revealed that the mechanoreceptor neurons on the fly labellum detect and assess the texture of food during feeding [12]. To identify the sensory structures and molecules which are indispensable for distinguishing fine food texture, we performed a candidate screening for mechanosensitive channel genes essential for sensation of tactile or proprioceptive information. Among these candidates, tmc is involved in the detection of tactile information from food [11], whereas inactive (iav) and nanchung (nan) sense vibration and proprioceptive stimuli in chordotonal organ (Cho) neurons [27,28]. When flies were allowed to choose between 0.25% and 0.4% agarose, we found that all the mutants tested here showed an impaired ability to discriminate fine difference of food hardness (Fig 2a). The flies lacking the iav gene even showed a reversed texture preference. We then compared the preference of iav mutant between 0.25% agarose and a range of other concentrations. These flies showed severe impairments in discriminating 0.3% to 0.5% agarose-containing food from 0.25% agarose-containing food but not to higher hardness (Fig 2b). This is strong evidence that iav is the mechanotransduction channel required in labellar mechanoreceptor neurons for fine food hardness detection. PPT PowerPoint slide

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TIFF original image Download: Fig 2. Single-dendritic labellum neurons discriminate substrates of different stiffness during feeding. a The preference of food hardness between 0.25% and 0.4% agarose of the mechanotransduction channel gene mutants (iav1, tmc-sgal4, tmc1, nangal4) in the two-way choice feeding assay. 10 mM sucrose was added to different concentrations of agarose. n = 33, 20, 27, 14 and 25 for each group. Statistical test: one-way ANOVA with Dunnett’s correction for multiple comparisons against the w1118 group; mean ± SEM. b The preference of food hardness of iav1 males between 0.25% and 5 different stiffness (0.25%, 0.35%, 0.4%, 0.45%, 0.5%) in the two-way choice feeding assay. 10 mM sucrose was added to different concentrations of agarose. n = 10, 9, 12, 9 and 13 for each group. Data are represented as mean ± SEM. c The preference of food hardness when sd-L neurons were silenced with kir2.1 in the two-way choice feeding assay. 10 mM sucrose was added to different concentrations of agarose. n = 21, 21 and 18 for each group. Statistical test: one-way ANOVA with Dunnett’s correction for multiple comparisons against the sd-L-SS > UAS-kir2.1 group; mean ± SEM. d Expression patterns for sd-L-SS (split-Gal4: vGluT-AD and iav-DBD) in the labellum and brain. Immunostaining used either anti-GFP and/or anti-Brp (magenta). Scale bar, 50 μm. Brain was counter-stained with the neuropil marker nc82 (magenta). Red arrow pointed to sd-L neurons (in the labellum) and its axon (in the brain). e PER assay of flies when sd-L neurons were activated using CsChrimson by exposure to 1 mW/cm2 light (595nm). Flies were tested with 20 mM sucrose. n = 29, 18, 14 and 21 for each group. Statistical test: one-way ANOVA with Dunnett’s correction for multiple comparisons against the sd-L-SS > UAS-CsChrimson with ATR group; mean ± SEM. f-h FlyPAD assay of flies when sd-L neurons were silenced with kir2.1. Flies were all starved for 24 h before assay. Both 0.25% and 0.4% agarose containing 10 mM sucrose. Cumulative sips numbers of sd-L-SS flies, n = 16 for each group (f). Cumulative sip numbers of UAS-kir2.1flies, n = 16 for each group (g). Cumulative sip numbers of sd-L-SS > UAS-kir2.1 flies, n = 15 for each group (h). For all analyses, statistical differences are represented as follows: ns, not significant, p > 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001. https://doi.org/10.1371/journal.pgen.1010562.g002

Activation of sd-L neurons in labellum promoted feeding We then wondered whether the direct activation of sd-L neurons had a positive impact on feeding behavior. To test this, we optogenetically activated sd-L neurons via a red-shifted channelrhodopsin, CsChrimson [35]. We found that w1118 male flies showed increased PER response with the increase of sucrose concentration, and 20 mM sucrose was a moderate concentration to induce reliable PER (S6a Fig). So we used 20 mM sucrose to test PER response during optogenetic activation. Remarkably, flies showed increased PER when sd-L neurons were activated by exposure to 1 mW/cm2 light (595nm) (Fig 2e), indicating the activation of sd-L neurons promoted flies feeding. To test the sugar concentration used in the two-way choice assay, we also tested 10mM sucrose stimulation. Flies also showed increased PER when sd-L neurons were activated (S6c and S6d Fig). Interestingly, activation of sd-L neurons alone optogenetically was insufficient to induce PER response. We used water stimuli as control during optogenetic activation before and after the sugar test, and almost no flies showed PER response to water with light on (S6b Fig). Considering that there was a neuron labelled with sd-L-SS on the leg which projected to VNC (S3a and S3c Fig), we removed all the legs of flies and tested the PER response. To test the sugar concentration used in the two-way choice assay, we also tested 10mM sucrose stimulation. Flies showed increased PER to both 10mM and 20mM sucrose when sd-L neurons were activated, and only activation of sd-L on the labellum was sufficient to enhance the PER (S6c and S6d Fig). Taken together, activation of sd-L neurons in labellum can promote feeding on sugar-containing food.

Identification of the second-order neurons of sd-L neurons Now we have demonstrated that sd-L neurons signal to the sweet-sensing neurons to promote the preference of hard food during feeding, which explains results of the two-way choice assay (Fig 1b). However, the flies’ haustellate mouthparts are adapted to suck liquid or sponge from liquefied food. We thus speculated that the activation of sd-L neurons would facilitate food ingestion. We next explored how the texture information sensed by sd-L neurons was integrated into the feeding motor control circuit. We first used trans-Tango, a method for anterograde trans-synaptic tracing [44], to identify putative second-order neurons of sd-L neurons. In flies bearing the sd-L-SS driver and the trans-Tango components, we observed dozens of neurons with their cell bodies located in the SEZ (Fig 4a), indicating that sd-L neurons mainly target the feeding control center of the brain. Then we screened thirty-four fly lines that showed a similar expression pattern in the SEZ with the trans-Tango labeled neurons. We found a driver R66B05-Gal4 that appeared to label the second-order neurons of sd-L neurons (Fig 4b). To validate this, we used the GRASP technique and observed intense reconstituted GFP signals between sd-L neurons and R66B05-labeling neurons in the SEZ (Fig 4c–4e), suggesting that sd-L neurons and R66B05 neurons may form synapses. PPT PowerPoint slide

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TIFF original image Download: Fig 4. R66B05 labels a subset of the second-order neurons of sd-L neurons. a Putative second order neurons of sd-L neurons revealed by trans-Tango (sd-L spilt gal4 > UAS-trans-tango; green, anti-GFP; magenta, anti-Brp). Scale bar, 50 μm. Magenta: nc82. b R66B05-Gal4 drove the expression of tdTomato (R66B05-Gal4 > UAS-CD4-tdTomato; red, anti-RFP; bule, anti-Brp) in the SEZ. Scale bar, 50 μm. Blue: nc82. c-e GRASP signal (green, anti-GFP) between sd-L and R66B05-LexA neurons in the SEZ. (c) sd-L spilt gal4 > UAS-CD4-spGFP1-10, lexAop-CD4-spGFP11; (d) R66B05-LexA > UAS-CD4-spGFP1-10, lexAop-CD4-spGFP11; (e)sd-L spilt gal4 > UAS-CD4-spGFP1-10, R66B05-LexA > lexAop-CD4-spGFP11. Scale bar, 50 μm. f Cumulative sip numbers of R66B05-Gal4 > UAS-kir2.1 flies in FlyPAD assay. Flies were all starved for 24 h before assay. Both 0.25% and 0.4% agarose contained 10 mM sucrose, n = 14 and 16 for each group. g PER assay of flies when R66B05 neurons were activated by CsChrimson by exposure to 1 mW/cm2 light (595nm). Flies were tested with 20 mM sucrose. n = 15, 18, 15 and 18 for each group. Statistical test: one-way ANOVA with Dunnett’s correction for multiple comparisons against the R66B05-Gal4 > UAS-CsChrimson with ATR group; mean ± SEM. h Co-localization between R66B05-Gal4 > UAS-CD4-tdTomato (red, anti-RFP) and vGluT-QF > QUAS-mCD8-GFP (green, anti-GFP) in the brain. White arrow pointed to the overlapping neurons. Scale bar, 50 μm. For all analyses, statistical differences are represented as follows: ns, not significant, p > 0.05; *, p < 0.05; **, p < 0.01; ***, p < 0.001; ****, p < 0.0001. https://doi.org/10.1371/journal.pgen.1010562.g004 To test whether R66B05 neurons were involved in food texture discrimination, we conducted FlyPAD assay. When R66B05 neurons were silenced, flies showed no feeding preference between 0.25% and 0.4% agarose (Fig 4f, S8a and S8b Fig), while parental control flies took more sips on 0.4% agarose than 0.25% agarose (Fig 2g and S8c–S8e Fig). Moreover, when R66B05 neurons were optogenetically activated, the flies showed higher PER percentage than their control lines, similar to what were observed in the sd-L neurons’ activation experiments (Figs 2e and 4g). The above results suggest that R66B05 are downstream neurons of sd-L neurons. But how do they participate in the feeding control? There are two possible mechanisms: 1, R66B05 neurons are interneurons that integrate sensory inputs from the peripheral, including those from sd-L neurons. 2, R66B05 neurons are themselves motor neurons that can be activated by sd-L neurons and promote feeding action. To differentiate the two possibilities, we performed co-localization experiment between 66B05-Gal4 and vGluT-QF, a glutaminergic neuron driver to label motor neurons in Drosophila [31]. These two neuronal populations partially co-localized (Fig 4h), indicating that some of the R66B05 driver labelled neurons are motor neurons in the SEZ. Although we can’t exclude the existence of interneurons in the R66B05 driver labelled neurons, this echoes our speculation that sd-L neurons may be the upstream of some interneurons in SEZ.

sd-L neurons synapse to subsets of motor neurons to control feeding Proboscis motoneurons are located in the SEZ and innervate muscle groups that potentially contributing to proboscis movement and food ingestion [45–47]. Upon a palatable gustatory stimulus, several groups of motor neurons control different steps of feeding, for examples, lifting the rostrum (MN9), extending the haustellum (MN4&9), extending the labellum (MN6), spreading the labella for food ingestion (MN9) [15,46,48], etc. Several driver lines were reported to label these MNs: MN9 are labelled by GMR18B07, MN4 are labelled by GMR45G01 and MN6 are labelled by GMR81B12 [15,46,48]. We then examined whether sd-L neurons formed synapses with these motor neurons. As expected, reconstituted GFP signals were found between sd-L neurons and these three MN types (Fig 5a–5c), suggesting that these motor neurons may receive inputs from sd-L neurons. PPT PowerPoint slide

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TIFF original image Download: Fig 5. Sd-L neurons project axons to motor neurons to control feeding action. a-c GRASP signal (green, anti-GFP) between sd-L neurons and MN4 (a), MN6 (b) and MN9 (c) neurons in the SEZ. (a) sd-L spilt gal4 > UAS-CD4-spGFP1-10 and R45G01-LexA > lexAop-CD4-spGFP11. (b) sd-L spilt gal4 > UAS-CD4-spGFP1-10 and R81B12-LexA > lexAop-CD4-spGFP11. (c) sd-L spilt gal4 > UAS-CD4-spGFP1-10 and R18B07-LexA > lexAop-CD4-spGFP11. Scale bar, 50 μm. d The labella spreading of w1118 flies when feeding on 0.25%, 0.4%, 0.6%, 0.8% or 1% agarose. All concentrations of agarose containing 100 mM sucrose. The red circle outlined the labellum lobe area. Scale bar, 100 μm. e-i Quanficatioin of labellum spreading area of w1118 (e), iav1 (f), sd-L-SS (g), UAS-kir2.1 (h) and sd-L-SS > UAS-kir2.1 (i) flies when fed with 0.25%, 0.4%, 0.6%, 0.8% or 1% agarose containing 100 mM sucrose. Data are represented as mean ± SEM; n = 8~12 for each group. https://doi.org/10.1371/journal.pgen.1010562.g005 During feeding, flies spread their two labellar lobes immediately when the labella touched the food [15] and this action is controlled by different sets of motor neurons [15,45–47]. We then tested whether labellum-spreading during feeding was affected by food hardness. With the increase of agarose concentration, the labellum-spread area of w1118 flies gradually increased (Fig 5d and 5e), indicating that flies need to extend and spread their labellum to a greater extent when encountering harder food. However, iav-mutated or sd-L neurons-silenced flies showed no differences in labellum-spreading when feeding agarose of different concentrations (Fig 5f–5i). These results support the notion that sd-L neurons can access the feeding-promoting motor neurons through direct or indirect way to promote both the preference and the single-choice behavior between sugar-containing 0.4% agarose and sugar-containing 0.25% agarose.

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[1] Url: https://journals.plos.org/plosgenetics/article?id=10.1371/journal.pgen.1010562

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