Abstract
How memories of past events influence behavior is a key question in neuroscience. The major associative learning center in Drosophila, the Mushroom Body (MB), communicates to the rest of the brain through Mushroom Body Output Neurons (MBONs). While 21 MBON cell types have their dendrites confined to small compartments of the MB lobes, analysis of EM connectomes revealed the presence of an additional 14 MBON cell types that are atypical in having dendritic input both within the MB lobes and in adjacent brain regions. Genetic reagents for manipulating atypical MBONs and experimental data on their functions has been lacking. In this report we describe new cell-type-specific GAL4 drivers for many MBONs, including the majority of atypical MBONs. Using these genetic reagents, we conducted optogenetic activation screening to examine their ability to drive behaviors and learning. These reagents provide important new tools for the study of complex behaviors in Drosophila.
Introduction
The Mushroom Body (MB) is the major site of associative learning in insects (reviewed in (1–3)). In the MB of each Drosophila brain hemisphere, multiple modalities of sensory stimuli are represented by the sparse activity of 2000 Kenyon cells (KCs) whose parallel axonal fibers form the MB lobes. The lobes are further divided into compartments by the innervation patterns of dopaminergic neuron (DAN) axons and mushroom body output neuron (MBON) dendrites. MBONs provide the convergence element of the MB’s three layer divergent-convergent circuit architecture and the outputs of the MBONs drive learned behaviors.
Whereas the dendrites of typical MBONs are strictly confined to the MB lobes, analysis of the Drosophila connectome (3, 4) revealed a new class of “atypical” MBONs, consisting of 14 cell types, that have part of their dendritic arbors outside the MB lobes, allowing them to integrate input from KCs with other information (3). Some atypical MBONs receive dendritic input from other MBONs. Several provide output onto dopaminergic neurons (DANs) that innervate the MB to participate in recurrent networks. At least five make strong, direct synaptic contact onto descending neurons that drive motor action. Three provide strong direct connections to tangential neurons of the fan-shaped body of the central complex. However, analysis of the behaviors mediated by atypical MBONs has been limited by the lack of genetic drivers needed to manipulate their activity.
Here we report the generation and characterization of cell-type-specific split-GAL4 driver lines for the majority of the atypical MBONs. We also provide driver lines for two typical MBON types for which cell-type-specific split-GAL4 drivers were not previously available, and improved drivers for several other MBONs. We demonstrate the use of these new split-GAL4 lines in two behavioral assays. Using a four-armed olfactory arena equipped with optogenetic LED panels (5, 6), we assessed the ability of the labeled neurons to act as the unconditioned stimulus in an olfactory learning assay, an indication of their regulation of the acitivity of DANs. We also measured the effects of their optogenetic activation on kinematic parameters relevant for olfactory navigation. These reagents provide important new tools for the study of complex behaviors in Drosophila.
Results and Discussion
Generation and characterization of split-GAL4 lines for MBONs
We generated split-GAL4 genetic driver lines corresponding to MBON cell type using well-established methods (7–10). The morphologies of the MBONs, produced by electron microscopic reconstruction, were used to search databases of light microscopic images to identify enhancers whose expression patterns might yield clean driver lines for that MBON when intersected (11, 12). We took advantage of an expanded set of starting reagents that were not available when we (13) generated the original set of split-GAL4 drivers for the MB cell types; in addition to the 7,000 GAL4 expression patterns described in (14), we had access to an additional 9,000 GAL4 expression patterns (10). A total of approximately 600 intersections were experimentally tested to generate the split-GAL4 lines reported here.
Figure 1 shows examples of expression patterns of some of the highest quality split-GAL4 lines. For many cell types we were able to identify multiple different split-GAL4 lines. The brain and ventral nerve cord expression patterns of all split-GAL4 lines are shown in Figure supplement 1 for atypical MBONs and Figure supplement 2 for typical MBONs. The original confocal stacks from which these Figures were generated, as well as additional image data, are available for download at https://splitgal4.janelia.org. Videos 1 and 2 provide examples of comparisons between light microscopic images from these lines and neuronal skeletons from the hemi-brain dataset (4) that were used to confirm the assignment of cell type identity. Figure supplement 3 summarizes what we consider to be the best available split-GAL4 lines for each of the MBON types identified by connectomics, based on a combination of the lines presented here and in previous studies.
For typical MBONs, we provide split-GAL4 lines for two cell types for which drivers were not described in (13), MBON21 and MBON23. We also provide improved lines for MBON04 and MBON19; previous drivers for MBON04 also had expression in other MBON cell types and our new line for MBON19 has less off-target expression (see (13) for previous lines).
For atypical MBONs we were able to generate multiple, independent driver lines for MBON20, MBON29, MBON30 and MBON33 that provide strong and specific expression. Several lines for MBON31 were generated, but they also stochastically express in MBON32. Lines for MBON26 and MBON35 have some off-target expression that might compromise their use in behavioral assays, but they should permit cell-type-specific imaging studies. We failed to generate lines for MBON24, MBON25, MBON27, MBON32 and MBON34; we identified 2 candidate lines for MBON28 (see Figure supplement 3).
Activation phenotypes of MBON lines
MBONs are the first layer of neurons that transform memories stored inside the MB into actions. MBONs can also provide input to the dendrites of the DANs that innervate the MB lobes, forming a recurrent network. To investigate these two aspects of MBON function, we used a four-armed olfactory arena equipped with LED panels for optogenetics (Figure 2A). A group of 20 starved flies that express CsChrimson in a particular MBON cell type was subjected to a series of optogenetic olfactory conditioning and memory tests, and then to six trials of activation in the absence of odors but with air-flow (Figure 2B). Using the same setup and similar protocols, we have previously characterized the dynamics of memories formed by optogenetically activating DAN cell types inneravting different MB compartments (6) and analyzed circuits downstream of the MBONs that promote upwind locomotion (15). Figure 2C displays the results of these behavioral experiments sorted by the mean memory score of each cell type in the final memory test. When possible, we ran multiple independent split-GAL4 lines for the same MBON cell type. The concurrence of phenotypes in these cases provides further evidence that the observed effects are due to the activation of that cell type rather than off-target expression or genetic background effects.
Training flies by paring odor presentation with activation of MBON21, using either of the two lines tested (SS81353 and SS81521), resulted in robust aversive memory (Figure 2C) as previously observed with another driver for this cell type that displayed weaker expression (see SS46348 in Figure supplement 2; (16)). Both driver lines for the atypical MBON29 similarly induced aversive memory. These MBONs are both cholinergic, have dendrites in the γ4 and γ5 compartments, and synapse onto the dendrites of DANs that respond to punitive stimuli such as PAM-γ3 and PPL1-γ1pedc (Figure 2C, Figure supplement 4; (3, 16)). In contrast, training flies with activation of MBON33 induced appetitive memory. MBON33 is also cholinergic but preferencially connects with octopaminergic neurons and reward-representing DANs. We noticed that confocal microscopy images of MBON33 visualized by split-GAL4 driven expression contains additional branches around the esophagus (Figure 1H), an area which was outside of EM hembrain volume. Since octopaminergic neurons arborize in this area (17), the connection between MBON33 and octopaminergic neurons might be more extensive than the previously described using the hemibrain data (3).
To explore kinematic parameters controlled by MBONs, we tracked the trajectories of individual flies during and after a 10-second optogenetic stimulus (Figure 2C). In these assays we observed some variability between lines for the same cell type, presumably due to difference in expression level or off-targeted expression. Nevertheless, the two lines for MBON21 showed similar patterns of kinematic variables: a low walking speed in the presence of the red activation light, a stimulus that caused elevated locomotion in genetic control flies, and then orientation toward upwind when the optogenetic stimulus concluded (Figures 2C and 3A-D). Similar phenotypes were observed with a driver for a combination of three glutamatergic MBONs: MBON01, MBON03 and MBON04 (MB011B; Figure 2C). Despite their common anatomical features and memory phenotypes, MBON21 and MBON29 modulated distinct motor parameters. Neither of the two lines for MBON29 changed walking speed or orientation toward upwind when activated, but they both increased angular motion at the onset of activation, similar to three lines for MBON26 (Figure 3E-G).
Finally, we asked if the MBON21, MBON29 and MBON33 lines that were able to serve as the unconditioned stimulus in memory formation also drove avoidance or attraction of corresponding valence. Previous studies and the results shown in Figures 2C indicated that these are not always shared phenotypes; for example, the set of glutamatergic MBONs in MB011B whose dendrites lie in the γ5 and β12 compartments, can drive downwind locomotion and avoidance behaviors (26–28) but do not induce aversive memory. We tested if flies expressing CsChrimson in each of these three MBON cell types prefer quadrants of the arena with red activating light during the first and second 30 s test periods (Figure 3H,I). When CsChrimson is expressed in MBON21 or MBON29, flies avoided illuminated quadrants of the arena. Conversely, CsChrismon activation in a line for MBON33 promoted attraction to illuminated quadrants, although this effect was observed only at the first test period. Thus, in the case of these three MBON cell types, memory formation and avoidance/attraction behaviors are correlated.
Concluding Remarks
We generated and anatomically characterized an improved set of genetic driver lines for MBONs and provide the first driver lines for atypical MBONs. We expect these lines to be useful in a wide range of studies of fly behavior. We demonstrate the suitability of these lines for behavioral analyses by showing that multiple independent lines for the same cell type gave consistent results when assayed for their ability to serve as the unconditioned stimulus in memory formation and to produce appetitive or aversive movements. MBON21, MBON29 and MBON33, characterized in this study, have dinstint features compared to well-studied MBONs that arborize in the same compartments. MBON21 and MBON29 form cholingergic connections to the dendrites of DANs known to respond to punishment, whereas other MBONs from the same compartments form glutamatergic connections with reward-representing DANs (Figure 4A).
While most sensory input to the MB is olfactory, the connectome revealed that two specific classes of Kenyon cells receive predominantly visual input. MBON19 provides the major output from one of these classes, KCα/βp, and about half of MBON19’s sensory input is estimated to be visual. MBON33 provides a major output from the other class of visual KCs, KCγd, with more than half of the sensory input to its dendrites in the MB estimated to be visual. The cell-type-specific driver lines we provide for MBON19 and MBON33 should facilitate studies of the behavioral roles of the two streams of visual information that pass through the MB.
The MB and the central complex (CX) are thought to play key roles in the most cognitive processes that the fly can perform including learning, memory, and spatial navigation. Two of the MBONs for which we generated cell-type-specific driver lines, MBON21 and MBON30, provide the strongest direct inputs to the CX from the MB (Figure 4B), while MBON30 receives over three percent of its input (450 synapses) from the CX cell type FR1. The genetic reagents we report here should advance studies of reinforcement signals in parallel memory systems, the role of visual inputs to the MB, and information flow from the MB to the CX.
Methods and Materials
Flies
Split-GAL4 lines were created as previously described (7). Flies were reared on standard cornmeal molasses food at 21-22°C and 50% humidity. For optogenetic activation experiments, flies were reared in the dark on standard food supplemented with retinal (Sigma-Aldrich, St. Louis, MO) unless otherwise specified, 0.2 mM all trans-retinal prior to eclosion and 0.4 mM all trans-retinal post eclosion. Female flies were sorted on cold plates and kept in retinal food vials for at least 1 day prior to be transferred to agar vials for 48-72 hours of starvation. Flies were 4-10 day old at the time of behavioral experiments.
Immunohistochemistry and imaging
Dissection and immunohistochemistry of fly brains were carried out as previously described (13). Each split-GAL4 line was crossed to the same Chrimson effector used for behavioral analysis. Full step-by-step protocols can be found at https://www.janelia.org/project-team/flylight/protocols. For single-cell labelling of neurons from selected split-GAL4 lines, we used the MultiColor FlpOut (MCFO) technique (29). Video 1 and Video 2 were produced using VVD Viewer (https://github.com/JaneliaSciComp/VVDViewer) to generate a video comparing light and EM data (hemibrain v1.2) for each cell type. Individual videos were then concatenated, and text added using Adobe Premiere Pro.
Optogenetics and olfactory learning assays
Groups of approximately 20 female flies were trained and tested at 25°C at 50% relative humidity in a fully automated olfactory arena for optogenetics experiments as previously described (5, 6, 30). The 627 nm peak LED light was used at 22.7 µW/mm2. The odors were diluted in paraffin oil (Sigma–Aldrich): Pentyl Acetate (PA; 1:10000) and Etyl Lactate (EL; 1:10000). Videography was performed at 30 frames per second with a 850 nm LED backlight with a 820 nm longpass filter and analyzed using the Flytracker (31) and Fiji (32).
Statistics
Statistical comparisons were performed using the Kruskal Wallis test followed by Dunn’s post-test for multiple comparison (Prism; Graphpad Inc, La Jolla, CA 92037). Appropriate sample size for olfactory learning experiment was estimated based on the standard deviation of performance index in a previous study using the same assay (6).
Connectomics
Information on connection strengths are taken from neuprint.janelia.org (hemibrain v1.2.1).
Acknowledgements
We thank the Janelia Fly Facility for help with fly husbandry and the FlyLight Project Team for dissection, histological preparation, and imaging of nervous systems.
We thank Janelia Project Technical Resources for carrying out EASI-FISH assays. Marisa Dreher (Dreher Design Studios, Inc.) assembled the videos and helped with figure design. Claire Managan segmented the neuron morphologies shown in the videos. Masayoshi Ito helped identify lines to use in intersections. We thank Vivek Jayaraman, Daisuke Hattori, Yichun Shuai and Toshihide Hige for comments on earlier drafts of the manuscript.
Supplemental Videos and Figures
Video 1: Comparison of light microscopic images of atypical MBONs with hemibrain skeletons of the corresponding cell types.
Video 2: Comparison of light microscopic images of typical MBONs with hemibrain skeletons of the corresponding cell types.
References
- 1.Mushroom body memoir: from maps to modelsNature Reviews Neuroscience 4:266–275https://doi.org/10.1038/nrn1074
- 2.The Drosophila Mushroom Body: From Architecture to Algorithm in a Learning CircuitAnnual Review of Neuroscience 43:465–484https://doi.org/10.1146/annurev-neuro-080317-0621333
- 3.The connectome of the adult Drosophila mushroom body provides insights into functioneLife 9https://doi.org/10.7554/eLife.62576
- 4.A connectome and analysis of the adult Drosophila central braineLife 9https://doi.org/10.7554/eLife.57443
- 5.An Aphid Sex AttractantInsect Systematics & Evolution 1:63–73https://doi.org/10.1163/187631270X00357
- 6.Dopaminergic neurons write and update memories with cell-type-specific ruleseLife 5https://doi.org/10.7554/eLife.16135
- 7.Genetic Reagents for Making Split-GAL4 Lines in DrosophilaGenetics 209:31–35https://doi.org/10.1534/genetics.118.300682
- 8.Refined spatial manipulation of neuronal function by combinatorial restriction of transgene expressionNeuron 52:425–436https://doi.org/10.1016/j.neuron.2006.08.028
- 9.Refinement of Tools for Targeted Gene Expression in DrosophilaGenetics 186:735–755https://doi.org/10.1534/genetics.110.119917
- 10.The VT GAL4, LexA, and split-GAL4 driver line collections for targeted expression in the Drosophila nervous systembioRxiv https://doi.org/10.1101/198648
- 11.PatchPerPixMatch for Automated 3d Search of Neuronal Morphologies in Light MicroscopybioRxiv https://doi.org/10.1101/2021.07.23.453511
- 12.A searchable image resource of Drosophila GAL4 driver expression patterns with single neuron resolutioneLife 12https://doi.org/10.7554/eLife.80660
- 13.The neuronal architecture of the mushroom body provides a logic for associative learningeLife 3https://doi.org/10.7554/eLife.04577
- 14.A GAL4-Driver Line Resource for Drosophila NeurobiologyCell Reports 2:991–1001https://doi.org/10.1016/j.celrep.2012.09.011
- 15.Neural circuit mechanisms for transforming learned olfactory valences into wind-oriented movementbioRxiv https://doi.org/10.1101/2022.12.21.521497
- 16.Input Connectivity Reveals Additional Heterogeneity of Dopaminergic Reinforcement in DrosophilaCurrent Biology 30:3200–3211https://doi.org/10.1016/j.cub.2020.05.077
- 17.A map of octopaminergic neurons in the Drosophila brainThe Journal of Comparative Neurology 513:643–667https://doi.org/10.1002/cne.21966
- 18.Inhibitory muscarinic acetylcholine receptors enhance aversive olfactory learning in adult DrosophilaeLife 8https://doi.org/10.7554/eLife.48264
- 19.Lateral axonal modulation is required for stimulus-specific olfactory conditioning in DrosophilaCurrent Biology 32:4438–4450https://doi.org/10.1016/j.cub.2022.09.007
- 20.Glutamate is an inhibitory neurotransmitter in the Drosophila olfactory systemProceedings of the National Academy of Sciences of the United States of America 110:10294–10299https://doi.org/10.1073/pnas.1220560110
- 21.Nitric oxide acts as a cotransmitter in a subset of dopaminergic neurons to diversify memory dynamicseLife 8https://doi.org/10.7554/eLife.49257
- 22.Coordinated and Compartmentalized Neuromodulation Shapes Sensory Processing in DrosophilaCell 163:1742–1755https://doi.org/10.1016/j.cell.2015.11.019
- 23.Reward signal in a recurrent circuit drives appetitive long-term memory formationeLife 4https://doi.org/10.7554/eLife.10719
- 24.Persistent activity in a recurrent circuit underlies courtship memory in DrosophilaeLife 7https://doi.org/10.7554/eLife.31425
- 25.A connectome of the Drosophila central complex reveals network motifs suitable for flexible navigation and context-dependent action selectioneLife 10https://doi.org/10.7554/eLife.66039
- 26.Mushroom body output neurons encode valence and guide memory-based action selection in DrosophilaeLife 3https://doi.org/10.7554/eLife.04580
- 27.A neural circuit for wind-guided olfactory navigationNature Communications 13https://doi.org/10.1038/s41467-022-32247-7
- 28.Hierarchical architecture of dopaminergic circuits enables second-order conditioning in DrosophilaeLife 12https://doi.org/10.7554/eLife.79042
- 29.Optimized tools for multicolor stochastic labeling reveal diverse stereotyped cell arrangements in the fly visual systemProceedings of the National Academy of Sciences of the United States of America 112:E2967–2976https://doi.org/10.1073/pnas.1506763112
- 30.An airflow olfactometer for measuring olfactory responses of hymenopterous parasitoids and other small insectsPhysiological Entomology 8:97–106https://doi.org/10.1111/j.1365-3032.1983.tb00338.x
- 31.Tracking for Quantifying Social Network of Drosophila MelanogasterComputer Analysis of Images and Patterns, Lecture Notes in Computer Science Berlin, Heidelberg: Springer :539–545https://doi.org/10.1007/978-3-642-40246-3_67
- 32.Fiji: an open-source platform for biological-image analysisNature Methods 9:676–682https://doi.org/10.1038/nmeth.2019
- 33.Neurotransmitter Classification from Electron Microscopy Images at Synaptic Sites in Drosophila MelanogasterbioRxiv https://doi.org/10.1101/2020.06.12.148775
- 34.Expansion-assisted iterative fluorescence in situ hybridization (EASI-FISH) in Drosophila CNS. doi: dx.doi.org/10.17504/protocols.io.5jyl8jmw7g2w/v1.
- 35.Three-dimensional reconstruction of brain-wide wiring networks in Drosophila at single-cell resolutionCurrent biology: CB 21:1–11https://doi.org/10.1016/j.cub.2010.11.056
Article and author information
Author information
Version history
- Preprint posted:
- Sent for peer review:
- Reviewed Preprint version 1:
- Reviewed Preprint version 2:
- Version of Record published:
Copyright
© 2023, Gerald M. Rubin & Yoshinori Aso
This article is distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use and redistribution provided that the original author and source are credited.
Metrics
- views
- 2,300
- downloads
- 179
- citations
- 9
Views, downloads and citations are aggregated across all versions of this paper published by eLife.