Drosophila gustatory projections are segregated by taste modality and connectivity
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Abstract
Abstract Gustatory sensory neurons detect caloric and harmful compounds in potential food and convey this information to the brain to inform feeding decisions. To examine the signals that gustatory neurons transmit and receive, we reconstructed gustatory axons and their synaptic sites in the adult Drosophila melanogaster brain, utilizing a whole-brain electron microscopy volume. We reconstructed 87 gustatory projections from the proboscis labellum in the right hemisphere and 57 from the left, representing the majority of labellar gustatory axons. Gustatory neurons contain a nearly equal number of interspersed pre-and post-synaptic sites, with extensive synaptic connectivity among gustatory axons. Morphology- and connectivity-based clustering revealed six distinct groups, likely representing neurons recognizing different taste modalities. The vast majority of synaptic connections are between neurons of the same group. This study resolves the anatomy of labellar gustatory projections, reveals that gustatory projections are segregated based on taste modality, and uncovers synaptic connections that may alter the transmission of gustatory signals.
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Cluster 2 corresponds to sugar GRNs.
“Thus, we conclude that cluster 2 corresponds to sugar GRNs, consistent with their previous assignment23, and cluster 3 corresponds to water GRNs.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [23]
The Results section (‘Different GRN classes can be identified by morphology and connectivity’) assigns group 2 to bitter GRNs, not sugar GRNs. It identifies group 4 as the hypothesized sugar-GRN group. The paper calls these clusters ‘groups,’ so its numbering does not support the cited assignment of cluster 2. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredGRN reconstructions on the left hemisphere are more complete.
“Because GRN reconstructions on the left hemisphere are more complete23, probably due to challenges imaging and reconstructing neurons at the brain’s periphery, we performed unilateral left hemisphere activation for all simulations, except for Extended Data Fig. 1d.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [23]
The Introduction and Discussion report that 83–96% of expected GRNs were reconstructed on the right hemisphere, compared with 54–63% on the left. The Results section (“GRN axons contain presynaptic and postsynaptic sites”) also says EM-volume misalignments prevented identification of additional left-hemisphere GRNs. The source therefore says the right, not the left, is more complete. (LLM, conf=0.90)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredCluster 3 corresponds to water GRNs.
“Thus, we conclude that cluster 2 corresponds to sugar GRNs, consistent with their previous assignment23, and cluster 3 corresponds to water GRNs.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [23]
In Results (‘Different GRN classes can be identified by morphology and connectivity’), the source assigns group 3 to candidate low-salt GRNs, not water GRNs. It identifies group 6 as the best match for water GRNs. These are the source’s own group numbers; the passage does not establish how they relate to clusters numbered in the citing paper. (LLM, conf=0.88)
Checked by a reasoning model — may be wrong.
Experimental — accuracy not yet measuredGustatory sensory neurons that respond to sugar, water and bitter tastes have been identified in the electron microscopy volume.
“Furthermore, gustatory sensory neurons that respond to sugar, water and bitter tastes have been identified in the electron microscopy volume23, permitting a detailed analysis of how these modalities interact.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [23]
The Results section identifies bitter, sugar, and water GRN groups in the electron microscopy volume by matching their anatomy to known taste classes. But it calls some assignments tentative, and the Discussion says the categories were identified by anatomical comparisons alone, not by directly testing the reconstructed neurons’ taste responses. (LLM, conf=0.85)
Experimental — accuracy not yet measuredGustatory receptor neurons on the body surface of the fly respond directly to tastants and project to the suboesophageal zone.
“Gustatory receptor neurons (GRNs) on the body surface of the fly, including the labellum (tip of the proboscis) or the legs, respond directly to tastants and project to the primary taste centre of the insect brain—the suboesophageal zone (SEZ)23,33–37.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [23]
The Introduction says gustatory neurons have cell bodies in sensilla on the body surface, detect taste compounds, and send projections from the labellum to the SEZ. The Results section on GRN axons also confirms the labellum-to-SEZ projection. The cited passages do not establish the sentence’s additional claim about GRNs on the legs projecting to the SEZ; no page numbers are provided in our copy. (LLM, conf=0.84)
Experimental — accuracy not yet measured
Extensive experimental analysis provides a ground truth for computational studies of the feeding initiation circuit.
“In addition, extensive experimental analysis provides a ground truth for computational studies4,5,23–32.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [23]
Bitter and Ir94e GRNs were identified previously by their distinctive morphology.
“Bitter and Ir94e GRNs were identified previously by their distinctive morphology23.”
From A Drosophila computational brain model reveals sensorimotor processing (2024) · cites this paper as [23]
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Self-citationA Drosophila computational brain model reveals sensorimotor processing
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“In addition, extensive experimental analysis provides a ground truth for computational studies 4,5,23–32 .”
BackgroundMethodInfluentialGenerating parallel representations of position and identity in the olfactory system
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Taste quality and hunger interactions in a feeding sensorimotor circuit
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Eichler, K., Hampel, S., Alejandro-García, A., Calle-Schuler, S. A., Santana-Cruz, A., Kmecova, L., Blagburn, J. M., Hoopfer, E. D., & Seeds, A. M. (2023) · doi:10.7554/elife.87602.1 · Cited by 1 · see citing works
- Authors
- Engert, S., Sterne, G. R., Bock, D. D., & Scott, K.
- Affiliations
- Howard Hughes Medical Institute (US)
- University of California, Berkeley (US)
- University of Vermont (US)
- Corresponding author
- Scott, Kristin
- Venue
- eLife
- Publisher
- eLife Sciences Publications, Ltd
- Published
- 2022-05-25
- Volume
- 11
- ISSN
- 2050-084X (ISSN-L)
- PMC
- PMC9170244
- OpenAlex
- W4281478671
- Cited by
- 38
- References
- 12
- Citations by year
- 2026: 4 · 2025: 10 · 2024: 11 · 2023: 11 · 2022: 1 · 2020: 1
- FWCI
- 3.65
- Type
- journal article
- Language
- en
- Open access
- gold
- doi.org
- Licence
- Locations
- eLife (publishedVersion, cc-by)
- bioRxiv (Cold Spring Harbor Laboratory) (acceptedVersion, cc-by-nc-nd)
- PubMed Central (publishedVersion, cc-by)
- PubMed (publishedVersion)
- DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
- Funders
- National Institutes of Health (R01DC013280, F32DK117671)
- Topics
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neurobiology and Insect Physiology Research
- Life Sciences › Neuroscience › Cellular and Molecular Neuroscience › Neuroscience and Neuropharmacology Research
- Health Sciences › Nursing › Nutrition and Dietetics › Biochemical Analysis and Sensing Techniques
- Keywords
- gustatory neurons, labellum, synaptic connectivity, axon reconstruction, Drosophila melanogaster, feeding behavior, neuronal clustering
- MeSH terms
- Animals, Drosophila, Drosophila melanogaster, Sensory Receptor Cells, Taste, Drosophila Proteins
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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