Elucidating the neural architecture that underlies sensorimotor transformations for behavior requires the ability to resolve and manipulate neural circuits with single-cell precision. With a tractable number of neurons and well-developed genetic tools, Drosophila melanogaster is an excellent animal in which to investigate the basic principles of sensorimotor processing. Recent electron microscopy datasets provide unprecedented synaptic resolution of approximately 100,000 neurons that comprise the adult D. melanogaster brain (Scheffer et al., 2020; Zheng et al., 2018). If coupled with resources that provide genetic access to single neurons, this detailed anatomy may be probed to study complex circuits underlying sensory processing and behavior.

The subesophageal zone (SEZ) of the adult insect brain plays a critical role in many sensory-driven behaviors. Defined as the brain tissue below the esophageal foramen, it is situated in a central location between the motor circuits of the ventral nerve cord (VNC) and the higher order brain regions of the supraesophageal zone (Ito et al., 2014). In Drosophila and other insects, the SEZ participates in many context-dependent motor actions, including feeding, grooming, and locomotion, with evidence suggesting that it is involved in action selection (Bidaye et al., 2020; Flood et al., 2013; Gordon and Scott, 2009; Hampel et al., 2017; Hampel et al., 2015; Mann et al., 2013; Manzo et al., 2012; Marella et al., 2006; Tastekin et al., 2015; Wang et al., 2004). It receives direct sensory input from axonal arbors of gustatory and mechanosensory peripheral neurons and indirect input from pheromone-sensing neurons (Ling et al., 2014; Thistle et al., 2012; Thorne et al., 2004; Toda et al., 2012; Wang et al., 2004; Weiss et al., 2011; Zhang et al., 2013). Two major outputs of the SEZ are descending neurons that convey information to the VNC and motor neurons that control the movement of the proboscis and antennae (McKellar et al., 2020; Namiki et al., 2018; Stocker et al., 1990). Recent work has delineated fascicle and neuropil-based columnar domains in the SEZ that are identifiable throughout development and has mapped sensory substructures in the SEZ in larvae and adults (Hartenstein et al., 2018; Kendroud et al., 2018; Miroschnikow et al., 2018). Despite these advances, the exploration of the function of SEZ neurons has been hindered by the lack of genetic access to individual cell types.

Previous studies of the function of SEZ cell types have relied on broad GAL4 lines or stochastic methods, which do not provide reliable access to individual neurons. Recent efforts using the split-GAL4 method in Drosophila have provided genetic access to libraries of single neurons in other brain regions, including the mushroom body, central complex, and lateral horn (Aso et al., 2014a; Dolan et al., 2019; Wolff and Rubin, 2018). In this intersectional method, two different enhancers are used to independently drive expression of either the GAL4 transcriptional activation domain (AD) or DNA-binding domain (DBD). These domains heterodimerize through leucine zipper fragments and drive transgene expression restricted to the intersection of the two expression patterns (Luan et al., 2006). Thus, split-GAL4 reagents may be rationally designed if they are constructed using enhancers with known expression patterns. To systematically probe the cellular anatomy of the SEZ and to enable genetic dissection of SEZ neural circuits, we set out to create a library of genetic reagents to label individual SEZ cell types using the split-GAL4 method.

Here, we report the creation of 277 split-GAL4 lines that we collectively term the SEZ Split-GAL4 Collection. We estimate that this collection targets nearly one third of all neurons with cell bodies in the SEZ of the adult Drosophila brain. Morphological clustering of the identified cell types reveals six layered (anterior to posterior) and stacked (inferior to superior) domains of organization in the SEZ. Furthermore, polarity analysis shows that many SEZ interneurons have inputs and outputs on the same processes, whereas SEZ projection neurons tend to be classically polarized, with inputs and outputs located in clearly distinct regions of the neuronal arbors. Taken together, the genetic reagents described here provide a valuable resource to investigate how diverse sensory inputs are processed by local SEZ circuitry to control specific behaviors.

Here, we describe the SEZ Split-GAL4 Collection, a library of 277 split-GAL4 lines covering 138 SEZ cell types, which affords unprecedented genetic access to SEZ neurons for behavioral and functional study. Our studies provide insight into the diversity of SEZ cell types and their organization into discrete anatomical domains. The SEZ Split-GAL4 Collection will enable further investigation of how local SEZ circuitry and ascending SEZ paths process sensory inputs and control specific behaviors.

Most of the SEZ Split-GAL4 lines are specific, with 149/277 lines classified as ideal or excellent. These lines will be useful to manipulate individual SEZ cell types for behavioral, functional, and imaging experiments. The remaining, less specific, lines (those belonging to the good or poor categories) will still be useful for imaging and as starting points for creating more specific reagents. Good and poor lines may be used to generate CDM masks to search for new hemidrivers to make further split-GAL4 lines. Alternatively, their expression patterns may be refined using Killer Zipper or three-way intersections with LexA or QF lines (Dolan et al., 2017; Shirangi et al., 2016). All lines in the SEZ Split-GAL4 Collection may be used to generate further tools including complementary split-LexA and split-QF reagents (Riabinina et al., 2019; Ting et al., 2011). Split-LexA and split-QF lines may be used in concert with the split-GAL4 lines reported here to simultaneously manipulate two independent neuronal populations for advanced intersectional experiments, including behavioral epistasis.

By combining insights from a single-cell transcriptome atlas with direct cell counts of SEZ neuromeres, we estimate that the SEZ Split-GAL4 Collection labels 30% of the ~1700 neurons in the SEZ. Because of the lack of stereotyped neuronal cell body positions in D. melanogaster, it is not possible to assign cell bodies to defined neuropil regions without a genetic marker. The advantage of our method of estimating SEZ neuron number is that it is based on analysis of the four genetically defined SEZ neuromeres, the tritocerebral, the mandibular, the maxillary, and the labial neuromeres. However, previous reports demonstrate that some deutocerebral commissures cross below the esophageal foramen, and therefore an unknown number of deutocerebral cell bodies may be part of the SEZ (Boyan et al., 2003; Ito et al., 2014). The limitations of our estimate of SEZ neuron number therefore include the inability to directly count cells derived from the tritocerebral neuromere, the inability to directly count neurons rather than glia, and the inability to assess deutocerebral contributions. Thus, our estimate of SEZ cell number is likely an underestimate. Once all SEZ neurons are densely reconstructed in an EM volume, direct counts of SEZ neuronal cell bodies obtained by EM will provide a more accurate assessment of SEZ neuron number. Regardless, the SEZ Split-GAL4 Collection targets 510 neuronal cell bodies, which represents a substantial improvement in our ability to precisely target SEZ cell types for functional and morphological analysis. We did not ascertain the neuromere or neuroblast of origin of the SEZ cell types in the SEZ Split-GAL4 Collection. However, recent work has established reliable anatomical criteria that define the boundaries between the four SEZ neuromeres and has mapped all secondary lineages of the SEZ (Hartenstein et al., 2018). Future efforts should focus on bridging previously identified fascicle, neuropil, and sensory domains into a common template or coordinate space to determine the neuromere and neuroblast origin of SEZ cell types.

Discovering and genetically targeting SEZ cell types required the use of registered light-level imagery and computer-assisted searching. We used four distinct strategies to identify 129 novel and 9 previously reported SEZ cell types in registered light-level imagery. Critically, each of these strategies allowed us to use CDM mask searching to identify additional hemidrivers with which to target each cell type of interest. CDM mask searching enabled combing of large datasets and greatly increased the ease and speed of split-GAL4 generation over previous methods (Otsuna et al., 2018). The same strategies can be leveraged to gain genetic access to yet-undiscovered SEZ cell types. The recent electron microscopy (EM) volumes of the D. melanogaster brain provide an avenue for identifying SEZ cell types that are not covered by the SEZ Split-GAL4 Collection. Notably, this approach awaits comprehensive reconstruction of the SEZ, a region that is not included in the recently published dense reconstruction of the ‘hemibrain’ volume (Scheffer et al., 2020). Another EM volume, ‘FAFB,’ provides imagery of an entire adult female fly brain at synaptic resolution and includes the SEZ (Zheng et al., 2018). Improvements in automated reconstruction of EM volumes coupled with large-scale human annotation should soon provide exhaustive reconstruction of the SEZ from which to identify additional SEZ cell types (Dorkenwald et al., 2020). Furthermore, available bridging registrations between EM volumes and light-level imagery should facilitate the identification of hemidrivers to target SEZ cell types discovered from EM reconstructions (Bates et al., 2020). Even without identifying additional SEZ cell types, the split-GAL4 reagents described will allow behavioral and functional evaluation of circuit hypotheses derived from EM imagery.

Our analyses of the SEZ Split-GAL4 Collection provide insight into the cellular architecture of the SEZ. To computationally probe the organization of the SEZ, we morphologically clustered 121 SEZ cell types using NBLAST (Costa et al., 2016). This approach reveals six cellular domains in the SEZ that are organized in a largely layered fashion from anterior to posterior. This layered structure is also hinted at by the recent description of SEZ neuropil domains throughout development from the larva to the adult (Kendroud et al., 2018). Based on anatomical position and the known function of a few SEZ neurons, it is tempting to speculate that different morphological clusters may participate in different behavioral functions. Group 1 contains projection neurons that innervate the region of the SMP surrounding the pars intercerebralis (PI), suggesting that group 1 neurons may impinge on neurosecretory neurons or function in energy and fluid homeostasis circuits. The proximity of group 1 interneurons to previously described interoceptive SEZ neurons (ISNs) (Jourjine et al., 2016) and ingestion neurons (IN1) (Yapici et al., 2016) supports this hypothesis. Group 2 contains Fdg, a feeding-related neuron, as well as cell types (indigo, tinctoria) that are located near pumping motor neurons (Manzo et al., 2012; McKellar et al., 2020), suggesting that group 2 neurons have roles in feeding sequence generation. Group 3 contains G2N-1, a candidate second-order gustatory neuron, and projection neurons that innervate recently described taste-responsive SLP regions (Kim et al., 2017; Snell et al., 2020), suggesting that group 3 may, in part, be composed of taste-responsive neurons. Many interneurons in group 4 are located near proboscis motor neurons that control rostrum protraction, haustellum extension, and labellar spreading (Kendroud et al., 2018; McKellar et al., 2020), indicating that group 4 members function in proboscis motor control. The proximity of neurons in group 5 to previously described stopping neuron MAN (Bidaye et al., 2014), and the inclusion of an antennal grooming neuron, suggests that group 5 neurons may participate in circuits that control grooming and stopping behaviors. Group 6 is located in the posterior SEZ and posterior slope, regions implicated in flight behaviors, including wing and neck control (Namiki et al., 2018; Robie et al., 2017). While we hypothesize potential behavioral functions for each supergroup, we readily acknowledge that the roles of the neurons described here are likely more diverse.

Our studies also shed light on information flow both within the SEZ and out of the SEZ to the higher brain. We identified 91 local interneurons, 30 projection neurons, 16 descending neurons, and 1 sensory neuron. Polarity analysis of 121/138 of the SEZ cell types covered by the SEZ Split-GAL4 Collection revealed that SEZ interneurons tend to have mixed or biased polarity while SEZ projection neurons tend to be classically polarized. Polarity analyses of the lateral horn, mushroom body, descending neurons, and protocerebral bridge identified few neurons with completely mixed polarity (Aso et al., 2014a; Aso et al., 2014b; Dolan et al., 2019; Namiki et al., 2018; Wolff and Rubin, 2018). Unlike these brain regions, the SEZ contains a large number of local interneurons. The mixed polarity of the SEZ interneurons argues for local and reciprocal connectivity between neurons, with information flowing in networks rather than unidirectional streams. Projection neurons, in contrast, may serve chiefly to pass information from highly interconnected SEZ circuits to other brain regions in a unidirectional manner. Notably, we identified many SEZ projection neurons that innervate the SMP—a region known to contain neurosecretory cell types. This may betray a role for acute taste detection or feeding circuit activation in the regulation of hormone secretion. In addition, the frequent innervation of the superior lateral protocerebrum and lateral horn by SEZ projection neurons may hint at the site of olfactory-gustatory synthesis. In contrast, we did not identify projection neurons that link the SEZ directly to the central complex or mushroom body. If dense reconstruction of EM volumes corroborates the lack of direct connectivity between the SEZ and these regions, information must be conveyed through indirect pathways. As an example, taste information influences local search behaviors during foraging, a task that is expected to involve the central complex (Haberkern et al., 2019). Indirect relay of taste information to the central complex to inform foraging behavior would be consistent with previous anatomical studies suggesting that the central complex receives diverse indirect sensory inputs (Pfeiffer and Homberg, 2014). Furthermore, the mushroom body is known to respond to taste, raising the possibility that taste information from gustatory sensory neuron axons in the SEZ must be relayed through yet another brain region before reaching mushroom body cell types (Harris et al., 2015). Thus, our analysis of SEZ neuron polarity indicates local SEZ processing and demonstrates direct pathways to a subset of higher brain regions.

Overall, the SEZ Split-GAL4 Collection represents a valuable resource that will facilitate the study of the SEZ. Our analysis of the collection reveals the cellular anatomy and polarity of individual SEZ neurons and their organization into six discrete domains in the SEZ. Coupled with emerging insights from reconstruction of EM volumes, the SEZ Split-GAL4 Collection will allow the use of genetic dissection to test circuit-level hypotheses about sensory processing and motor control in the SEZ.

Detailed information about the split-GAL4s and available imagery is included in a supplemental database (Supplementary file 1). Image data are publicly available and all lines may be ordered at http://splitgal4.janelia.org.

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Author details

1. Gabriella R Sterne

   1. University of California Berkeley, Berkeley, United States
   2. Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Software, Visualization, Writing - original draft

   For correspondence

   sternegr@berkeley.edu

   Competing interests

   none

   "This ORCID iD identifies the author of this article:" 0000-0002-7221-648X

2. Hideo Otsuna

   Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States

   Contribution

   Formal analysis, Methodology, Resources, Software, Writing - review and editing

   Competing interests

   none

3. Barry J Dickson

   1. Janelia Research Campus, Howard Hughes Medical Institute, Ashburn, United States
   2. Queensland Brain Institute, University of Queensland, Queensland, Australia

   Contribution

   Conceptualization, Funding acquisition, Project administration, Supervision, Writing - review and editing

   Competing interests

   none

   "This ORCID iD identifies the author of this article:" 0000-0003-0715-892X

4. Kristin Scott

   University of California Berkeley, Berkeley, United States

   Contribution

   Conceptualization, Funding acquisition, Project administration, Supervision, Writing - review and editing

   For correspondence

   kscott@berkeley.edu

   Competing interests

   none

   "This ORCID iD identifies the author of this article:" 0000-0003-3150-7210

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