Origin of wiring specificity in an olfactory map revealed by neuron type–specific, time-lapse imaging of dendrite targeting

  1. Kenneth Kin Lam Wong
  2. Tongchao Li  Is a corresponding author
  3. Tian-Ming Fu
  4. Gaoxiang Liu
  5. Cheng Lyu
  6. Sayeh Kohani
  7. Qijing Xie
  8. David J Luginbuhl
  9. Srigokul Upadhyayula
  10. Eric Betzig
  11. Liqun Luo  Is a corresponding author
  1. Department of Biology, Howard Hughes Medical Institute, Stanford University, United States
  2. Howard Hughes Medical Institute, Janelia Research Campus, United States
  3. Advanced Bioimaging Center, Department of Molecular and Cell Biology, University of California, Berkeley, United States
  4. Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, United States
  5. Chan Zuckerberg Biohub, United States
  6. Departments of Molecular and Cell Biology and Physics, Howard Hughes Medical Institute, Helen Wills Neuroscience Institute, University of California, United States

Abstract

How does wiring specificity of neural maps emerge during development? Formation of the adult Drosophila olfactory glomerular map begins with the patterning of projection neuron (PN) dendrites at the early pupal stage. To better understand the origin of wiring specificity of this map, we created genetic tools to systematically characterize dendrite patterning across development at PN type–specific resolution. We find that PNs use lineage and birth order combinatorially to build the initial dendritic map. Specifically, birth order directs dendrite targeting in rotating and binary manners for PNs of the anterodorsal and lateral lineages, respectively. Two-photon– and adaptive optical lattice light-sheet microscope–based time-lapse imaging reveals that PN dendrites initiate active targeting with direction-dependent branch stabilization on the timescale of seconds. Moreover, PNs that are used in both the larval and adult olfactory circuits prune their larval-specific dendrites and re-extend new dendrites simultaneously to facilitate timely olfactory map organization. Our work highlights the power and necessity of type-specific neuronal access and time-lapse imaging in identifying wiring mechanisms that underlie complex patterns of functional neural maps.

Editor's evaluation

When a neuron is born it correlates with where it targets in the neuropil and this has been best demonstrated in the olfactory lobe of Drosophila. This important study uses sophisticated genetics and advanced live imaging to provide a compelling description of how neuronal dendrites explore the target field, eliminate excessive branches, and assort into the correct region during development. In the process, it develops valuable tools. The study brings us closer to a comprehensive understanding of how the birth order of a neuron translates to dendrite patterning within the Drosophila antennal lobe circuit.

https://doi.org/10.7554/eLife.85521.sa0

eLife digest

The brain’s ability to sense, act and remember relies on the intricate network of connections between neurons. Organization of these connections into neural maps is critical for processing sensory information. For instance, different odors are represented by specific neurons in a part of the brain known as the olfactory bulb, allowing animals to distinguish between smells.

Projection neurons in the olfactory bulb have extensions known as dendrites that receive signals from sensory neurons. Scientists have extensively used the olfactory map in adult fruit flies to study brain wiring because of the specific connections between their sensory and projection neurons. This has led to the discovery of similar wiring strategies in mammals. But how the olfactory map is formed during development is not fully understood.

To investigate, Wong et al. built genetic tools to label specific types of olfactory projection neurons during the pupal stage of fruit fly development. This showed that a group of projection neurons directed their dendrites in a clockwise rotation pattern depending on the order in which they were born: the first-born neuron sent dendrites towards the top right of the antennal lobe (the fruit fly equivalent of the olfactory bulb), while the last-born sent dendrites towards the top left.

Wong et al. also carried out high-resolution time-lapse imaging of live brains grown in the laboratory to determine how dendrites make wiring decisions. This revealed that projection neurons send dendrites in all directions, but preferentially stabilize those that extend in the direction which the neurons eventually target. Also, live imaging showed neurons could remove old dendrites (used in the larvae) and build new ones (to be used in the adult) simultaneously, allowing them to quickly create new circuits.

These experiments demonstrate the value of imaging specific types of neurons to understand the mechanisms that assemble neural maps in the developing brain. Further work could use the genetic tools created by Wong et al. to study how wiring decisions are determined in this and other neural maps by specific genes, potentially yielding insights into neurological disorders associated with wiring defects.

Introduction

Organization of neuronal connectivity into spatial maps occurs widely in the nervous systems across species (Luo and Flanagan, 2007; Cang and Feldheim, 2013; Luo, 2021). For example, in the retinotopic map of the visual system, nearby neurons in the input field project axons to nearby neurons in the target field (Cang and Feldheim, 2013). Such a continuous organization preserves spatial relationships in the visual world. Contrary to retinotopy, the olfactory glomerular map consists of discrete units called glomeruli in which input neurons connect with the cognate output neurons based on neuronal type rather than soma position (Mombaerts et al., 1996; Gao et al., 2000; Vosshall et al., 2000). This discrete map represents a given odor by the combinatorial activation of specific glomeruli. Whereas continuous maps are readily built using gradients of guidance cues (Cang and Feldheim, 2013), how glomeruli are placed at specific locations in discrete maps is less clear (Murthy, 2011). Understanding the developmental origins of these neural maps is fundamental for deciphering the logic of their functional organization through which information is properly represented and processed.

The adult Drosophila olfactory map in the antennal lobe (the equivalent of the vertebrate olfactory bulb) has proven to be a powerful model for studying mechanisms of wiring specificity, thanks to the type-specific connections between the presynaptic olfactory receptor neurons (ORNs) and the cognate postsynaptic projection neurons (PNs). Molecules and mechanisms first identified in this circuit have been found to play similar roles in the wiring of the mammalian brain (e.g. Hong et al., 2012; Berns et al., 2018; Pederick et al., 2021). Assembly of the fly olfactory map begins with dendritic growth and patterning of PNs derived primarily from the anterodorsal (adPNs) and lateral (lPNs) lineages and born with an invariant birth order within each lineage (Jefferis et al., 2001; Jefferis et al., 2004; Marin et al., 2005; Yu et al., 2010; Lin et al., 2012; Figure 1A and B). This patterning creates a prototypic olfactory map, prior to ORN axon innervation, indicative of the PN-autonomous ability to target dendrites into specific regions. However, earlier studies could only unambiguously follow the development of one single PN type – DL1 PNs (Jefferis et al., 2004). It remains unclear to date how the prototypic olfactory map is organized and what cellular mechanisms PN dendrites use to achieve targeting specificity (Figure 1C1-2). The initial map formation is further complicated by circuit remodeling during which embryonic-born PNs used in both the larval and adult circuits reorganize their neurites (Marin et al., 2005). How embryonic-born PNs coordinate remodeling with re-integration into the adult circuit is not known (Figure 1C3).

Figure 1 with 2 supplements see all
Organization and development of the adult olfactory circuit in Drosophila.

(A, B) Timeline (A) and schematic illustration (B) of Drosophila olfactory circuit development. Green, red, and blue circles denote the birth of embryonic-born anterodorsal projection neuron (adPN), larval-born adPN, and larval-born lPN, respectively. At the onset of metamorphosis, the larval-specific olfactory circuit degenerates; larval olfactory receptor neurons (ORNs) die while embryonic-born adPNs prune their larval-specific processes and re-extend new processes into the adult-specific olfactory circuit. In the adult-specific olfactory circuit, projection neuron (PN) dendrites extend first and form a prototypic map. This is followed by an extension of ORN axons and synaptic partner matching between cognate PN dendrites and ORN axons to form a mature map. Solid and open arrowheads in A indicate onset of innervation for PN dendrites and ORN axons, respectively. (C) Overview of this study investigating the logic of dendritic patterning (C1; see Figures 3 and 4) as well as cellular mechanisms of dendrite targeting specificity (C2; see Figures 6 and 7) and re-wiring (C3; see Figure 8) that contribute to the developmental origin of the adult Drosophila olfactory map. (D) Staining of fixed brains at indicated stages showing dendrite development of adPNs (VT033006+ run+ ; labeled in yellow) and lPNs (VT033006+ run–; labeled in cyan). As run-FLP is expressed before 0 h APF in adPN but not lPN neuroblasts, we can use it to label adPNs and lPNs with two distinct colors using an intersectional reporter (see Materials and methods for the genotype). Yellow arrowheads in (D1) mark larval- and adult-specific dendrites of adPNs in larval- and adult-specific antennal lobes, respectively. Cyan arrowheads in (D3) denote specific targeting of lPN dendrites at the opposite ends of the dorsomedial-ventrolateral axis. (D1): N=12; (D2): N=7; (D3): N=17; (D4): N=10; (D5): N=12. Common notations in this study: Unless otherwise indicated, all images in this and subsequent figures are partial z projections of confocal stacks of representative images. N indicates the number of antennal lobes imaged. Antennal lobe neuropils are revealed by N-Cadherin (Ncad; in blue) staining. Adult-specific (developing) antennal lobe is outlined with a white solid line. Larval-specific antennal lobe is outlined with an orange line (dashed line used to denote the degeneration stage) and is distinguished from the developing antennal lobe by the more intense nc82 staining as shown in Figure 1—figure supplement 1 (nc82 channel not shown here). Asterisks (*) indicate PN cell bodies, which are outside the antennal lobe neuropil (and sometimes appear on top because of the z-projections). Arrowheads mark PN dendrites. Arrows mark PN axons projecting towards higher olfactory centers (see Figure 1—figure supplement 2 for PN axons at their targets in the mushroom body and lateral horn). h APF: hours after puparium formation; h ALH: hours after larval hatching. DL: dorsolateral; DM: dorsomedial; VM: ventromedial; VL: ventrolateral. Scale bar = 10 µm.

Here, we set out to explore the origin of the olfactory map by performing a systematic and comparative study of PN dendrite development at type-specific resolution in vivo, and two-photon– and adaptive optical lattice light-sheet microscope–based time-lapse imaging of PN dendrites in early pupal brain explants. As our overarching goal is to understand how the wiring specificity between ORNs and PNs arises, we focus on PNs that project to single glomeruli. Neurons from the lateral lineage that innervate multiple glomeruli or project to other regions of the adult brain (Lin et al., 2012) are not studied here. Our study uncovers wiring logic that directs PN dendrites to create an organized olfactory map, dendritic branch dynamics that lead to directional selectivity, and a novel re-wiring mechanism that facilitates timely olfactory map formation. These wiring strategies used in the initial map organization lay the foundation of precise synaptic connectivity between PNs and ORNs in the final glomerular map.

Results

Overview of Drosophila olfactory circuit development at a lineage-specific resolution

We first described the development of the Drosophila olfactory circuit using pupal brains double-labeled for adPNs and lPNs (Figure 1D; see the genetic design in Figure 2). At the onset of metamorphosis (0 hr after puparium formation; 0 hr APF), the adult-specific antennal lobe (also referred to as ‘developing antennal lobe’) remained relatively small, located dorsolateral and posterior to the larval-specific antennal lobe (also referred to as ‘degenerating antennal lobe’) (Figure 1D1). As PN dendrites continued to grow and innervate the developing antennal lobe, its size increased considerably (Figure 1D13). By 12 hr APF, PNs already appeared to be sorting their dendrites into specific regions to form a prototypic map, as revealed by the heterogeneous patterning of lPN dendrites (arrowheads in Figure 1D3). From 21 hr to 50 hr APF, dendrites of adPNs and lPNs gradually segregated and eventually formed intercalated but non-overlapping glomeruli (Figure 1D45). The development of the adult-specific antennal lobe partially overlapped with the degeneration of the larval-specific antennal lobe, as indicated by fragmentation of the larval-specific dendrites of embryonic-born PNs at 3 hr APF (Figure 1D2). This gross characterization at the resolution of two PN lineages was consistent with earlier studies (Jefferis et al., 2004; Marin et al., 2005). However, the resolution was not sufficiently high to answer the questions we raised in the Introduction (Figure 1C).

Figure 2 with 3 supplements see all
Expanded genetic toolkit for dual-color, type-specific labeling of projection neurons (PNs).

(A) tSNE plot of PN single-cell transcriptomes, color-coded according to CR45223 expression level in [log2(CPM +1)], where CPM stands for transcript counts per million reads. Zoom-in of boxes in the tSNE plot (left) is shown on the right, and color-coded according to PN types and developmental stages. (B) Dot plot showing the expression of acj6, vvl, CR45223, CG14322, lov, and tsh in 0 hr APF PNs arranged according to their birth order and lineage (green: embryonic-born anterodorsal projection neuron (adPNs); red: larval-born adPNs; blue: larval-born lPNs). Unit of expression is [log2(CPM +1)] as in A. Data from panels A are B are from Xie et al., 2021. (C) Birth orders of adPNs and lPNs summarized by Lin et al., 2012; Yu et al., 2010 and genetic tools used to access them. Left: Accessible PN types are colored. Circles beneath the PN types denote QF2/GAL4 drivers used to access them. Asterisks beneath the PN types denote access by MARCM. Gray arrowhead marks neuroblast (NB) rest. Right: Genetic tools. Inset shows the combinatorial use of QF2/FLP and GAL4 (linked by dashed lines) for comparative analyses of dendrite development of two groups of PNs in the same animal. (D) Schematic of glomerular projections of QF2/GAL4-accessible PNs in the adult antennal lobe. Indicated glomeruli are color-coded based on the genetic tools used to access them. See the color code in C. (E, F) Schematic of intersectional logic gates for dual-color labeling of PNs. See Figure 2—figure supplement 2 for newly generated FLP-out reporters.

Figure 3 with 4 supplements see all
Birth order–dependent spatial patterning of anterodorsal projection neuron (adPN) dendrites in the developing antennal lobe.

(A) Confocal images of fixed brains at indicated stages showing dendrite development of adPNs (acj6+; labeled in green) and DL1 adPNs (71B05+; labeled in yellow). Right column of A1 shows a zoom-in of the dashed box. The labeling of acj6+ adPNs outlines the developing antennal lobe and is used in dual-color AO-LLSM imaging later (see Figure 7A–C). White arrowheads in (A1) mark dendrites overshooting the antennal lobe. (A1): N=14; (A2): N=12; (A3): N=14; (A4): N=6; (A5): N=4; (A6): N=4. (B) Confocal images of fixed brains at indicated stages showing dendrite development of DL1/DA3 adPNs (CG14322+; labeled in yellow) and DC2 adPNs (91G04+; labeled in magenta). As 91G04-GAL4 labels some embryonic-born projection neurons (PNs) from 0 to 6 hr APF, their neurites are found in the larval-specific antennal lobe (B1, 2). Right column of (B1) shows a zoom-in of the dashed box. White arrowhead in (B4) denotes the more ventrally targeted DL1/DA3 dendrites. (B1): N=6; (B2): N=5; (B3): N=12; (B4): N=4; (B5): N=7; (B6): N=2. (C) Confocal images of fixed brains at indicated stages showing dendrite development of DC3/VA1d adPNs (Mz19+ acj6+; labeled in red) and DA1 lPNs (Mz19+ acj6–; labeled in cyan). (C1): N=14; (C2): N=6; (C3): N=4; (C4): N=10; (C5): N=10; (C6): N=6; (C7): N=4. (D) Confocal images of single-cell MARCM clones (in yellow) of DL1 PNs (D1–3), mid-late larval-born adPNs (D4–6), and late larval-born adPNs (D7–9) in 12 hr APF pupal brains, generated by heat shocks (hs) at indicated times. Three biological samples are shown for each of the indicated adPN cohorts. D1–3: N=5; D4–6: N=4; D7–9: N=8. (E) Summary of wiring logic of larval-born adPN dendrites to form an olfactory map in the 12 hr APF developing antennal lobe. See Figure 1 legend for common notations.

Expanded genetic toolkit for type-specific labeling of PNs during early pupal development

To reveal how PN dendrites initiate olfactory map formation at the high spatiotemporal resolution, we needed genetic access to specific PN types during early pupal development. From our recently deciphered single-cell PN transcriptomes (Xie et al., 2021), we searched for genetic markers that are expressed strongly and persistently in single or a few PN types across pupal development. This transcriptome-instructed search led to the identification of CR45223 (in place of this non-coding gene, we used the adjacent CG14322 that exhibits nearly identical expression pattern), lov, and tsh (Figure 2A and B; Figure 2—figure supplement 1).

Next, using CRISPR/Cas9, we generated knock-in transgenic QF2 expression driver lines in which T2A-QF2 (or T2A-FLP for intersection) was inserted immediately before the stop codon of the endogenous gene (Figure 2—figure supplement 2). The self-cleaving peptide T2A allows QF2 to be expressed in the same pattern as the endogenous gene (Diao and White, 2012). With these new QF2 lines together with existing GAL4 lines that label additional PN types (Xie et al., 2019), we now have an expanded toolkit accessing PNs ranging from early- to late-born PNs, from adPN to lPN lineages, and from PNs with neighboring glomerular projections to those with distant projections in the adult antennal lobe (Figure 2C and D). As QF2/QUAS and GAL4/UAS expression systems operate orthogonally to each other (Potter et al., 2010; Riabinina et al., 2015), we crossed our QF2 lines with existing GAL4 lines for simultaneous labeling of distinct PN types in the same brain (see inset in Figure 2C). This combinatorial use of driver lines permitted comparative analyses of the development of distinct PN types with minimal biological and technical variations (Supplementary file 1).

To limit driver expression only in PNs, we applied intersectional logic gates (AND and NOT gates) using our newly generated conditional reporters genetically encoding either mGreenLantern, Halo tags, and/or SNAP tags (Kohl et al., 2014; Sutcliffe et al., 2017; Campbell et al., 2020; Figure 2E and F; Figure 2—figure supplement 3). These reporters can be broadly used in other systems. Finally, we used MARCM (Lee and Luo, 1999) to label PNs that remain inaccessible due to a lack of drivers (Figure 2C; discussed in Figure 3).

Early larval-born adPN dendrites initially share similar targeting regions

Using the new genetic tools, we first re-visited the dendrite development of DL1 PNs—the first larval-born adPN type—using pupal brains double-labeled for DL1 PNs (labeled by 71B05-GAL4) and adPNs (Figure 3A). Consistent with our previous study (Jefferis et al., 2004), DL1 PNs already showed robust dendritic growth at the wandering third instar larval stage (Figure 3—figure supplement 1A). At 0 hr APF, DL1 PN dendrites extended radially outwards from the main process, reaching nearly the entire developing antennal lobe and often overshooting it (white arrowheads in Figure 3A1), likely surveying the surroundings. By 6 hr APF, most of the dendrites already occupied the dorsolateral (DL) corner of the antennal lobe (Figure 3A2). As the antennal lobe continued to grow, this dorsolateral positioning of the DL1 PN dendrites remained largely unchanged (Figure 3A36). From 21 hr APF onwards, the dendrites underwent progressive refinement: they were restricted into a smaller area by 30 hr APF (Figure 3A45), and eventually formed a compact, posterior glomerulus by 50 hr APF (Figure 3A6 showing a single z section).

To assess whether other PN types follow the same developmental trajectory, we next examined CG14322+ PNs, which include DL1 PNs and DA3 PNs—the first and second larval-born adPN types, respectively. In the same brain, we also labeled with a different fluorophore DC2 PNs—the third larval-born adPN type (Figure 3B). The dendritic pattern of DL1/DA3 PNs appeared indistinguishable from that of DL1 PNs from 0 hr to 12 hr APF (compare the yellow channel of Figure 3B1–3 with Figure 3A1–3), suggesting that DL1 and DA3 PN sent dendrites to the same region in the antennal lobe. We began to see differences in 21 hr APF pupal brains in which DL1/DA3 PN dendrites not only occupied the dorsolateral region but also spread ventrally (white arrowhead in Figure 3B4; compare with Figure 3A4). The more ventrally targeted dendrites likely belong to DA3 PNs. This suggests that ~21 hr APF marks the beginning of dendritic segregation of DL1 and DA3 PNs. By 30 h APF, DL1 and DA3 dendrites were clearly separable (Figure 3B5), which respectively formed more posteriorly and anteriorly targeted glomeruli at 50 hr APF (Figure 3B6; see single z sections in Figure 3—figure supplement 1C).

Next, we focused on the third-born—DC2 PNs labeled by 91G04-GAL4 (Figure 3B). This GAL4 labeled additional embryonic-born adPNs from 0 hr to 6 hr APF, but the expression in these PNs diminished afterward. As embryonic-born adPNs do not have any dendrites in the developing antennal lobe at 0 hr APF (discussed in Figure 8), dendrites found in the antennal lobe should belong to the larval-born DC2 PNs. Like DL1/DA3 PNs, DC2 PNs initiated radial dendritic extension across the antennal lobe at 0 hr APF (Figure 3B1; Figure 3—figure supplement 1B). Notably, DL1/DA3 and DC2 PN dendrites exhibited substantial overlap from 0 hr to 12 hr APF and shared a similar targeting region at the dorsolateral corner from 6 hr to 12 hr APF (Figure 3B1–3). It was not until 21 hr APF that DL1, DA3, and DC2 dendrites began to segregate from each other along both medial-lateral and anterior-posterior axes (Figure 3B45). By 50 hr APF, the DC2 glomerulus was separated from DL1/DA3 glomeruli by intermediate glomeruli (Figure 3B6).

In summary, dendrites of consecutively larval-born DL1, DA3, and DC2 adPNs (here collectively named ‘early larval-born adPNs’; see its definition in next section) develop in a similar fashion and share a similar targeting region at early pupal stages (0–12 hr APF). This is then followed by their segregation into distinct regions close to their adult glomerular positions during mid-pupal stages (21–50 hr APF).

Larval-born adPNs with distant birth order send dendrites to distinct regions

The analysis of early larval-born adPNs (Figure 3A and B) led us to hypothesize that larval-born adPNs might use their birth order to coordinate dendrite targeting during early pupal stages. If this were true, we would expect dendrites of larval-born adPNs with distant birth order to occupy distinct regions. To test this hypothesis, we compared dendrite-targeting regions of early larval-born adPNs with those of later-born adPNs.

We first examined DC3/VA1d adPNs (referred to as ‘mid-early larval-born adPNs’) using Mz19-GAL4 (Figure 3C). This GAL4 is expressed in three PN types from 24 hr APF to adulthood: DC3 adPNs, VA1d adPNs, and DA1 lPNs (Jefferis et al., 2004). To distinguish adPNs from lPNs, we previously adopted an FLP-out strategy labeling Mz19+ PNs with either GFP or RFP based on their lineages and studied dendrite segregation and refinement during mid-pupal stages (Li et al., 2021; Figure 3C4–7). However, the weak GAL4 expression before 24 hr APF prevented us from visualizing any dendrites at earlier stages. To overcome this, we incorporated Halo and SNAP chemical labeling (Kohl et al., 2014) in place of the immunofluorescence approach. This modification substantially extended the detection to developmental stages as early as 12 hr APF (Figure 3C1). We found that, from 12 hr to 21 hr APF, DC3/VA1d PN dendrites targeted the ventrolateral (VL) corner of the antennal lobe (Figure 3C14). Thus, early (DL1/DA3/DC2) and mid-early (DC3/VA1d) larval-born adPN dendrites occupy distinct regions at 12 hr APF.

As we did not have reliable drivers to access other later-born PNs at early pupal stages, we turned to MARCM (Lee and Luo, 1999) to generate heat shock-induced single-cell clones of PNs born at different times (Figure 3—figure supplement 2). We used GH146-GAL4(IV), a PN driver that labels the majority of PN types, including later-born adPNs (Figure 3—figure supplement 2D–E), with a tight temporal control of heat shock and analyzed heat shock-induced animals that were among the first to form puparium to minimize the effects of unsynchronized development among individual animals (see Materials and methods for details). These optimizations permitted a systematic clonal analysis at higher PN type-specific resolution that correlates with birth time.

Based on birth timing that corresponds to the heat shock time we applied to induce single-cell MARCM clones, we assigned larval-born adPNs to approximate temporal cohorts: (1) heat shock at 0–24 hr ALH (after larval hatching): first-born (DL1), (2) heat shock at 42–48 hr ALH: early-born (DL1, DA3, DC2, and D), (3) heat shock at 66–72 hr ALH: mid-late born (VM7v, VM7d, VM2, DM6, and VA1v), and (4) heat shock at 96–100 hr ALH: late-born (DM6, VA1v, DL2v, DL2d) (Figure 3E1). We assigned DC3/VA1d PNs labeled by Mz19-GAL4 to the mid-early cohort because they are born between the early and mid-late adPNs. We note that DM6 and VA1v PNs were assigned to both cohorts of mid-late and late-born adPNs, reflecting the nature of short birth timing differences and overlaps between adjacent cohorts. Using this strategy, we could also label lPNs born at different times and assigned them into approximate temporal cohorts (Figure 3—figure supplement 2F).

Clonal analysis revealed that, at 12 hr APF, the first-born DL1 adPNs sent dendrites to the dorsolateral corner of the antennal lobe as expected (Figure 3D1–3). By contrast, dendrites of mid-late larval-born adPNs occupied a large region on the medial/dorsomedial (M/DM) side (Figure 3D46). The dendritic arborization patterns of these PNs varied widely, most likely because they belonged to different PN types. Intriguingly, late larval-born adPN dendrites targeted the peripheral, dorsomedial (abbreviated as pDM) corner where the staining of the pan-neuropil marker N-Cadherin was relatively weak (Figure 3D7–9). The weak staining implies that this area is less populated by PN dendrites (the major constituent of the antennal lobe neuropil at this stage), possibly because (1) this area is not innervated by many PNs and/or (2) the dendrites of late-born PNs innervate later and remain less elaborate than earlier-born PNs (we will explore this later).

Together, our data (Figure 3A–D) suggest that larval-born adPNs with adjacent birth order send dendrites to similar regions of the developing antennal lobe whereas those with distant birth order send dendrites to distinct regions (Figure 3E2,3). Notably, the birth order of the examined PNs does not specify dendrite targeting randomly (Figure 3E4). Rather, the stereotyped dendritic pattern in the prototypic map correlates with the birth order in an organized manner (rotating clockwise in the right hemisphere when viewed from the front; anti-clockwise in the left: early↔DL; mid-early↔VL; mid-late↔M/DM; late↔pDM). One can, therefore, infer at least the approximate birth order of a larval-born adPN based on its initial dendrite targeting, and vice versa.

As the antennal lobe is a 3D structure, we also visualized PN dendrite targeting in the 12 hr APF map with 3D rendering generated from z stacks with rotation along the y-axis (Figure 3—video 1). We found that, along the short anterior-posterior axis (spanning about 20 µm), PN dendrites were located primarily on the periphery of the antennal lobe, whereas the center housed the axon bundle projecting out of the antennal lobe. Some dendrites could reach almost the entire depth, suggesting active exploration of the surroundings in many directions. While 3D projections provide rich details in depth and different viewing angles, we did not find an apparent relationship between birth order and dendrite targeting along the anterior-posterior axis, at least for the examined PN types at 12 hr APF. Thus, the approximate 2D projection (Figure 3E24) conveys the logic of dendrite patterning effectively.

Dendrite targeting timing of larval-born adPN depends on birth order

Having provided evidence for birth order–dependent spatial patterning of larval-born adPN dendrites, we next asked whether the timing of dendritic extension and targeting is also influenced by birth order. We noticed that the extent of dendritic innervation of 0 hr APF first-born DL1 adPNs resembled that of 6 hr APF mid-late born adPNs (compare Figure 3—figure supplement 3A1–4 with Figure 3—figure supplement 3B5–8). Such a resemblance was also seen between 0 hr APF mid-late and 6 hr APF late-born adPNs (compare Figure 3—figure supplement 3B1–4 with Figure 3—figure supplement 3C). Quantitative analyses of the exploring volume of dendrites and the number of terminal branches showed that, at 0 hr APF, DL1 PN dendrites were more elaborate than mid-late born PN dendrites (Figure 3—figure supplement 3F). By 6 hr APF, the mid-late born appeared to catch up, showing an extent of innervation comparable to DL1 PNs.

We next examined when the dendrites reach their targeting regions. We found that whereas early larval-born adPNs (DL1, DA3, DC2) concentrated their dendrites to the dorsolateral corner by 6 hr APF (Figure 3B2; Figure 3—figure supplement 3A5–8), later-born PNs concentrated their dendrites to the medial/dorsomedial or peripheral dorsomedial side at 12 hr APF (Figure 3D4-9; Figure 3—figure supplement 3B5-8, C). Thus, our results suggest larval-born adPN dendrites innervate and pattern the antennal lobe using a ‘first born, first developed’ strategy.

Contribution of lineage to early PN dendritic patterning

Both lineage and birth order of PNs contributes to the eventual glomerular choice of their dendrites (Jefferis et al., 2001). What is the involvement of lineage in the prototypic map formation? Do lPN dendrites pattern the developing antennal lobe following similar rules as adPNs? To characterize lPN dendrite development at type–specific resolution, we used tsh-GAL4 to genetically access DA1/DL3 lPNs, and MARCM clones of lPNs as a complementary approach (Figure 4). We focused on the dendritic patterns of tsh+ DA1/DL3 lPNs from 0 hr to 12 hr APF as tsh-GAL4 labeled additional PNs from 21 hr APF onwards (Figure 4A46; Figure 4—figure supplement 1B4–6; Figure 4—figure supplement 2; Figure 2—figure supplement 1).

Figure 4 with 3 supplements see all
Birth order–dependent spatial patterning of lPN dendrites in the developing antennal lobe.

(A) Confocal images of fixed brains at indicated stages showing dendrite development of DL1/DA3 adPNs (CG14322+; labeled in yellow) and DA1/DL3 lPNs (tsh+; labeled in cyan). Right column of A1 shows a zoom-in of the dashed box. (A1): N=8; (A2): N=4; (A3): N=6; (A4): N=10; (A5): N=4; (A6): N=5. (B) MARCM clones (in cyan) of early (B1–3) and late (B4–6) larval-born lPNs in 12 hr APF pupal brains, generated by heat shocks (hs) at indicated times. In (B3), (B5), and (B6), single-cell clones of anterodorsal projection neuron (adPN) (yellow arrowheads) and lPN (cyan arrowheads) lineages were simultaneously labeled. Three biological samples are shown for each of the indicated lPN cohorts. B1–3: N=4; B4–6: N=6. (C) Summary of wiring logic of larval-born lPN dendrites to form an olfactory map in the 12 hr APF developing antennal lobe. (D) Summary of determination of dendrite targeting of larval-born PNs by lineage and birth order. See Figure 1 legend for common notations.

Figure 5 with 3 supplements see all
Establishment of an explant system for time-lapse imaging of olfactory map formation.

(A) Schematic of the anatomical organization of the olfactory circuit in early pupal brain (0–3 hr APF). Green, red, and blue denote embryonic-born adPN, larval-born anterodorsal projection neuron (adPN), and larval-born lPN, respectively. MB: mushroom body; LH: lateral horn. (B) Schematic of explant culture system for early pupal brains. Wells created in the Sylgard plate from which brains were imbedded are shown in blue. (C) Schematic of explant culture and imaging system for early pupal brains. (D) Top: Schematic of morphological changes of brain lobes from 0 hr to ~15 hr APF during normal development. Bottom: Morphologies of a brain explant dissected at 3 hr APF and cultured for 0 hr ex vivo and cultured for 22 hr ex vivo. (E) Two-photon time-lapse imaging of adPNs (VT033006+ run+ ; labeled in magenta) and lPNs (VT033006+ run–; labeled in green) in pupal brain dissected at 3 hr APF and cultured for 0–22 hr ex vivo. Arrowheads mark dynamic but transient dendritic protrusions of lPNs in E1, 2, and extensive dendritic innervation of lPNs in (E3). Arrows in (E3) mark axonal innervation of lPNs in the mushroom body calyx and lateral horn. N=3. (F) Confocal images of antennal lobes labeled by VT033006+ projection neurons (PNs) (in green) at 0 hr (F1), 6 hr (F2), and 12 hr (F3) APF in vivo. Confocal images of antennal lobes labeled by VT033006+ PNs in pupal brains were dissected at 0 hr APF and cultured for 12 hr (F4) and 24 hr (F5) ex vivo. (F1): N=6; (F2): N=5; (F3): N=6; (F4): N=8; (F5): N=8. (G) Dendrite targeting regions of DL1 PNs (71B05+; in yellow; G1) and DA1/DL3 PNs (tsh+; in cyan; G2) in the antennal lobes in pupal brains dissected at 0 hr APF and cultured for 24 hr ex vivo. Antennal lobes are revealed by N-Cadherin (Ncad; in blue) staining. (G1): N=5; (G2): N=6. See Figure 1 legend for common notations.

Examination of pupal brains double-labeled with DA1/DL3 lPNs (referred to as ‘middle larval-born lPNs’) and DL1/DA3 adPNs revealed that, like the early larval-born adPNs, dendritic growth of DA1/DL3 lPNs was evident by the wandering third instar larval stage (Figure 4—figure supplement 1A). At this stage, most DA1/DL3 lPN dendrites innervated the antennal lobe and intermingled with those of DL1/DA3 adPNs. From 0 hr to 12 hr APF, despite a high degree of overlap among those dendrites that explored the surroundings, DA1/DL3 lPN dendrites primarily targeted an area ventrolateral to those of DL1/DA3 adPNs (Figure 4A1–3; see 3D rendering in Figure 4—video 1). Such a spatial distinction was also observed between middle larval-born adPNs and lPNs in 0 hr and 6 hr APF pupal brains where occasionally single-cell clones from both lineages were simultaneously generated by MARCM (Figure 3—figure supplement 3D1–4, 7–10). Thus, at least some adPNs and lPNs sort their dendrites into distinct regions very early on regardless of birth timing.

Next, we used MARCM to ask if lPNs born earlier and later than DA1/DL3 lPNs would send dendrites to regions different from that of DA1/DL3 lPNs. We found that dendrites of early-born lPNs primarily occupied the medial/dorsomedial side of the antennal lobe (Figure 4B1–3); we note that adPNs born at the same time sent dendrites to the dorsolateral side (see yellow arrowhead in Figure 4B3). Also, in contrast to the ventrolateral targeting of middle-born lPN dendrites, late-born lPNs sent dendrites to the dorsomedial corner (Figures 4B46). Like larval-born adPNs, late-born lPNs innervated the antennal lobe later than earlier-born lPNs (Figure 3—figure supplement 3D7–12–E, G).

These data suggest that, at early pupal stages, lPN dendrites pattern the developing antennal lobe following similar rules as larval-born adPNs: adjacent birth order → similar dendrite targeting; distant birth order → distinct dendrite targeting; ‘first born, first developed.’ However, unlike the correlation of birth order and target positions in a rotational manner for adPNs (Figure 3E), the lPN dendritic map formation appears binary: early↔M/DM; middle↔VL; late↔DM (Figure 4C). Our type-specific characterization corroborated with the gross examination of the lPN dendrites as previously reported (Jefferis et al., 2004): at 12 hr APF, lPN dendrites mostly occupied the opposite corners along the dorsomedial-ventrolateral axis, leaving the middle of the axis largely devoid of lPN dendrites (arrowheads in Figure 1D3).

In summary, we propose that lineage and birth order of larval-born PNs contribute to their dendrite targeting in a combinatorial fashion (Figure 4D). The wiring logic of PN dendrites in the developing antennal lobe can, therefore, be represented by [lineage, birth order]=dendrite targeting; one can deduce the unknown if the other two are known.

An explant system for time-lapse imaging of PN development at early pupal stages

So far, we have identified wiring logic governing the initial dendritic map formation (Figures 3 and 4) by examining specifically labeled neuron types in the fixed brain at different developmental stages. To examine dendrite targeting at the higher spatiotemporal resolution, we established an early-pupal brain explant culture system based on previous protocols (Özel et al., 2015; Rabinovich et al., 2015; Li and Luo, 2021; Li et al., 2021), and performed single- or dual-color time-lapse imaging with two-photon microscopy as well as adaptive optical lattice light-sheet microscopy (AO-LLSM) (Figure 5A–C). The following lines of evidence support that our explant system recapitulates key features of in vivo olfactory circuit development.

First, during normal development, the morphology of the brain lobes changes from spherical at 0 hr APF to more elongated rectangular shapes at 15 hr APF (Rabinovich et al., 2015). After 22 hr ex vivo culture, the spherical hemispheres of brains dissected at 3 hr APF became more elongated, mimicking ~15 hr APF in vivo brains characterized by the separation of the optic lobes from the central brain (Figure 5D).

Second, dual-color, two-photon imaging of PNs every 20 min for 22 hr revealed that lPNs in 3 hr APF brains initially produced dynamic but transient dendritic protrusions in many directions, followed by extensive innervation into the antennal lobe (arrowheads in Figure 5E1–3; Figure 5—video 1). In higher brain centers, lPN axons clearly showed direction-specific outgrowth of collateral branches into the mushroom body calyx as well as forward extension into the lateral horn (arrows in Figure 5E3), thus resembling in vivo development (Figure 1—figure supplement 2).

Third, larval-specific dendrites observed in 0 hr APF brains cultured for 12 hr ex vivo (orange arrowhead in Figure 5F4) were no longer seen in those cultured for 24 hr ex vivo (Figure 5F5), indicative of successful pruning and clearance of larval-specific dendrites. Also, the size of the developing antennal lobe in the brains cultured for 24 hr ex vivo increased considerably (Figure 5F5). These imply that olfactory circuit remodeling (degeneration of larval-specific processes and growth of adult-specific processes) proceeds normally, albeit at a slower rate (compare with Figure 5F1–3).

Fourth, dendrites from genetically identified DL1 and DA1/DL3 PNs targeted to their stereotyped locations in the antennal lobe in 0 hr APF brains cultured for 24 hr ex vivo (Figure 5G), mimicking in vivo development (Figure 4A).

Finally, the segregation of dendrites of PNs targeting to neighboring proto-glomeruli could be recapitulated in brains dissected at 24 hr APF and cultured for 8 hr (Figure 5—figure supplement 1; Figure 5—video 2). Specifically, despite constant dynamic interactions among dendrites that explore the surroundings (arrowheads in Figure 5—figure supplement 1A2–4), DC3/VA1d and DA1 PNs exhibited a 1–2 µm increase in the distance between centers of the two dendritic masses and a substantial decrease in the overlap of their core targeting regions (Figure 5—figure supplement 1B–D). Taken together, these data support that the explant culture and imaging system established here reliably captures key neurodevelopmental events starting from early pupal stages.

Single-cell, two-photon imaging reveals active dendrite targeting

Our observation in fixed brains revealed that dendrites of DL1 adPNs transition from a uniform extension in the antennal lobe at 0 hr APF to concentration at the dorsolateral corner of the antennal lobe at 6 hr APF (Figure 3A). To identify mechanisms of dendrite targeting specificity that could be missed in static developmental snapshots, we performed two-photon time-lapse imaging of single-cell MARCM clones of DL1 PNs in 3 hr APF brains (Figure 6; Figure 6—figure supplement 1; Figure 6—video 1). Although we did not have a counterstain outlining the antennal lobe, we could use the background signals to discern the orientation of DL1 PNs in the brain (Figure 6—figure supplement 1A). The final targeting regions relative to the antennal lobe revealed by post hoc fixation and immunostaining confirmed proper dendrite targeting (yellow arrowhead in Figure 6A10; Figure 6—figure supplement 1B–C).

Figure 6 with 2 supplements see all
Two-photon time-lapse imaging reveals active dendrite targeting.

(A) Two-photon time-lapse imaging of MARCM-labeled DL1 projection neuron (PN) (pseudo-colored in yellow) in a brain dissected at 3 hr APF and cultured for 21 hr ex vivo (A1–9). Arrowheads in A4–6 denote protrusions of dendritic branches towards the dorsolateral direction. After 21 hr culture, the explant was fixed and immuno-stained for N-Cadherin (Ncad; in blue) to outline the developing antennal lobe (A10). Yellow and cyan arrowheads indicate DL1 PN dendrites and processes of other GH146+ cells, respectively. (B) Neurite tracing of DL1 PN at the beginning of live imaging (3 hr APF + 0 hr ex vivo). Dendrites are categorized based on the directions to which they extend and color-coded accordingly. (C) Left: Quantification of the percentage of dendritic volume in indicated direction during the time-lapse imaging period reveals a transitional phase during which dendrites were found in only two out of the four directions. Right: Schematic of the initial, transitional, and final phases during the course of targeting. ‘½’ denotes the reduction of available trajectory directions by half. Timestamp 00:00 refers to HH:mm; H, hour; m, minute. See Figure 6—source data 1. (D) Quantification of the percentage of DL1 PN dendritic volume in an indicated direction in 3 hr APF cultured brains at the beginning (0 hr ex vivo) and at/near the end of imaging (18 hr ex vivo). DL1 PN sample size = 3. t-test; *p<0.05. Timestamp 00:00 refers to HH:mm; H, hour; m, minute. (E) Quantification of the percentage of the sum of DL1 PN dendritic volume in indicated directions throughout the entire imaging time. DL1 PN sample size = 3. (F) Bulk dendrite dynamics of DL1 PN in Figure 6A. Each row represents bulk dendritic dynamics in the indicated direction (color-coded as in Figure 6B) across the 21 hr imaging period. Each block represents a 20 min window. Bulk extension (in green) and retraction (in magenta) events are defined as dendrites extending and retracting more than 2 μm between two consecutive time windows. The first and last six consecutive windows refer to the initial and final phases of imaging. (G) Quantification of the number of bulk extension and retraction events in the dorsolateral direction during the initial and final phases of imaging. DL1 PN sample size = 3. t-test; *p<0.05.

Using DL1 PN in Figure 6A (pseudo-colored in yellow; Figure 6—video 1) as an example, we observed that the PN initially extended dendrites in every direction (Figure 6A1–3), like what we observed in fixed tissues (Figure 3A1). The first sign of active targeting emerged at 2 hr 20 min ex vivo when DL1 PN began to generate long, albeit transient, dendritic protrusions in the dorsolateral direction; these selective protrusions were more prominent at 3 hr ex vivo (arrowheads in Figure 6A4–6). The dorsolateral targeting continued to intensify, leading to the formation of a highly focal dendritic mass seen at 13 hr ex vivo (arrowhead in Figure 6A8). As the dendrites reached the dorsolateral corner and explored locally, the change in shape appeared less pronounced (Figure 6A9).

To quantitatively characterize the active targeting process, we categorized the bulk dendritic masses emanating from the main process according to their targeting directions: DL, DM, VM, and VL (Figure 6B). During the initial phase, the percentage of dendritic volume in each direction varied from 10% to 40% (Figure 6C and D), indicative of active exploration with little targeting specificity. Despite these variations, the total amount of dendritic mass seen in the VM direction over the entire imaging time (area under the graph of Figure 6C) was the smallest across all samples examined (Figure 6E). The initial phase of exploration in every direction was followed by a ~4 hr transitional phase during which DL1 PNs predominantly extended dendrites in 2 of the 4 directions (Figure 6C; Figure 6—figure supplement 1D–E). One of the 2 directions was always DL whereas the other was either DM or VL but never VM. In the final phase, DL1 PN dendrites always preferred DL out of the two available directions. Lastly, we analyzed the bulk dendritic movements. We defined bulk extension and retraction events when dendrites respectively extended and retracted more than 2 μm between two consecutive time frames. The analyses showed a striking shift from frequent extension and retraction towards stabilization, reflecting the pre- and post-targeting dynamics, respectively (Figure 6F and G).

Hence, long-term two-photon imaging of single-cell DL1 PNs revealed that dendrite targeting specificity increases over time via active targeting in a specific direction and stepwise elimination of unfavorable trajectory choices (see summary in Figure 7F1–3).

Figure 7 with 4 supplements see all
AO-LLSM time-lapse imaging reveals cellular mechanisms of dendrite targeting specificity.

(A–C) AO-LLSM imaging of DL1 projection neurons (PNs) (71B05+; labeled in yellow) and anterodorsal projection neurons (adPNs) (acj6+; labeled in blue) in cultured brains dissected at 3 hr (A), 6 hr (B), and 12 hr (C) APF. Zoom-in, single z-section images of (A1), (B1), and (C1) (outlined in dashed boxes) are shown in A2, B2 and C2, respectively. (D) Single dendritic branch dynamics of 3 hr (D1), 6 hr (D2), and 12 hr (D3) DL1 PNs shown in A–C. Terminal branches are analyzed and categorized based on the directions in which they extend. Their speeds are color-coded using purple-gray-green gradients (negative speeds, retraction; positive speeds, extension). Individual branches are also assigned into four categories: stable, transient, emerging, and retracting (color-coded on the right; see Figure 7—figure supplement 1A). Each block represents a 30s window. Each row represents individual branch dynamics across the 15 min imaging period. (E) Quantification of the abundance (in percentage) of DL1 PN stable branches in indicated direction at 3 hr, 6 hr, and 12 hr (E1). Average speed of DL1 PN stable branches in indicated direction at 3 hr, 6 hr, and 12 hr (E2). DL1 PN sample size: 3 hr=4; 6 hr=3; 12 hr=3. Error bars, SEM; t-test; One-way ANOVA; *p<0.05; n.s., p≥0.05. SEM, standard error of the mean; n.s., not significant. See Figure 7—source data 1. (F) Summary of mechanisms underlying the emergence of dendrite targeting specificity revealed by two-photon and AO-LLSM imaging of DL1 PN dendrites.

AO-LLSM imaging suggests a cellular mechanism underlying dendrite targeting specificity

To capture fast dynamics of single dendritic branches, we performed dual-color adaptive optical lattice sheet microscopy (AO-LLSM) imaging (Chen et al., 2014; Wang et al., 2014; Liu et al., 2018) of PNs every 30 s for 15 min, following a protocol we recently established (Li et al., 2021; Li and Luo, 2021). We selected 3 hr, 6 hr, and 12 hr APF pupal brains double-labeled with DL1 PNs and bulk adPNs (Figure 7A–C; Figure 7—videos 1–3). The labeling of adPNs with GFP outlined PN cell bodies and the developing antennal lobe but not the degenerating one, presumably because the GFP in larval-specific dendrites was quickly quenched upon glial phagocytosis (Marin et al., 2005).

In the 15 min imaging window, we observed four types of terminal branches regardless of neuronal types or developmental stages: (1) stable branch that existed throughout the entire imaging time, (2) transient branch that was produced and eliminated within the imaging window, (3) emerging branch that was produced after imaging began, and (4) retracting branch that was eliminated within the imaging period (Figure 7—figure supplement 1A). To examine if terminal branch dynamics exhibit any directional preference, we assigned the branches according to their targeting directions (Figure 7D). Extension and retraction events were defined when the speed exceeded 0.5 μm/min. Terminal branches were selected for analyses as branches closer to the main process were too dense to resolve. Figure 7D1-3 showed the dynamics of ~15 randomly selected terminal branches in each direction from the representative 3 hr, 6 hr, and 12 hr APF DL1 PNs (Figure 7A–C).

Quantitative analyses revealed that at 3 hr APF, DL1 PNs constantly produced, eliminated, extended, and retracted dendritic branches (Figure 7A, Figure 7D1, Figure 7—video 1). Even stable branches were not immobile. Rather, they spent comparable amounts of time extending and retracting at ~1.5 μm/min (Figure 7—figure supplement 1A1, 1B). Transient, emerging, and retracting branches had similar, but more variable speeds, ranging from 1 to 2.5 μm/min. Although there was no correlation between targeting direction and frequency/speed of extension/retraction, the number of stable branches in the VM direction was significantly lower than in other directions across all 3 hr DL1 PN samples examined (Figure 7E1). This suggests that even though dendritic branches were developed in every direction at the early stages, those branches in the VM direction were short-lived and might be eliminated by retraction. The direction-dependent stability/lifespan of dendritic branches on the timescale of seconds uncovered from AO-LLSM imaging explains why bulk dendrites in unfavorable trajectories failed to persist in long-term two-photon imaging.

From 6 hr to 12 hr APF, DL1 PNs no longer manifested direction-specific branch de/stabilization (Figure 7B–C, Figure 7D2–3, Figure 7—videos 2–3). At the same developmental stage, stable branches in one direction appeared indistinguishable from those in other directions in terms of abundance, frequency, and speed (Figure 7D2–3, Figure 7—figure supplement 1C–D). This suggests that the entire dendritic mass tends to stay in equilibrium upon arrival at target regions. At 12 hr APF, the abundance of stable branches of DL1 PNs was the highest (Figure 7D–E1). Also, the stable branches of 12 hr APF DL1 PNs moved at a significantly lower speed (~1 μm/min) (Figure 7E2) and spent more time being stationary than those at 3 hr and 6 hr (Figure 7—figure supplement 1B–D). The reduced branch dynamics at 12 hr APF is consistent with observations from two-photon imaging showing fewer bulk extension/retraction events in the final phase of targeting (Figure 6F–G). Despite the slowdown, dendritic arborization was evident in terminal branches of 12 hr APF DL1 PNs (Figure 7—figure supplement 1E), suggesting that PN dendrites are transitioning from simple to complex branch architectures. Although it remains unclear if there is a causal relationship between reduced branch dynamics and increased structural complexity, we propose that both contribute to the sustentation of dendrite targeting specificity.

In summary, AO-LLSM imaging reveals that PNs selectively stabilize branches in the direction towards the target and destabilize those in the opposite direction, providing a cellular basis of dendrite targeting specificity. Upon arrival at the target, the specificity is sustained through branch stabilization in a direction-independent manner (summarized in Figure 7F4–7).

Embryonic-born PNs timely integrate into an adult olfactory circuit by simultaneous dendritic pruning and re-extension

In earlier sections, we uncovered wiring logic of larval-born PN dendritic patterning and cellular mechanisms of dendrite targeting specificity used to initiate olfactory map formation (Figures 37). In this final section, we focused on embryonic-born PNs, which participate in both larval and adult olfactory circuits by reorganizing their processes (Marin et al., 2005). Our previous study demonstrates that embryonic-born PNs prune their larval-specific dendrites during early metamorphosis (Marin et al., 2005; Figure 1D13). Here, we examined when and how embryonic-born PNs re-extend dendrites used in the adult olfactory circuit.

It is known that γ neurons of Drosophila mushroom body (γ Kenyon cells) and sensory Class IV dendritic arborization (C4da) neurons prune their processes between 4 hr and 18 hr APF and show no signs of re-extension at 18 hr APF (Lee et al., 2000; Watts et al., 2003; Lee et al., 2009). Do embryonic-born adPNs follow a similar timeframe? We first examined developing brains double-labeled for embryonic-born DA4l/VA6/VA2 adPNs (collectively referred to as ‘lov+ PNs’) and early larval-born DC2 adPNs (Figure 8A; Figure 8—figure supplement 1). We found that, by 12 hr APF, lov+ PNs already sent adult-specific dendrites to a region ventromedial to DC2 PN dendrites (green arrowhead in Figure 8A3; see 3D rendering in Figure 8—video 1). This implies that lov+ PNs have already caught up with DC2 PNs on dendrite development at this stage, and the re-extension of lov+ PN dendrites must have happened even earlier. Indeed, we observed lov+ PN dendrites innervated the developing antennal lobe extensively at 6 hr APF (Figure 8A2). Such innervation was not observed at 0 hr APF (Figure 8A1). After 12 hr APF, the time course of lov+ PN dendrite development was comparable to that of DC2 PNs (Figure 8A4–6).

Figure 8 with 6 supplements see all
Embryonic-born projection neurons (PNs) timely participate in olfactory map formation via simultaneous pruning and re-extension.

(A) Confocal images of fixed brains at indicated stages showing dendrite development of lov+ PNs (embryonic-born; labeled in green) and 91G04+DC2 PNs (larval-born; labeled in magenta). As 91G04-GAL4 also labels some embryonic-born PNs from 0 to 6 hr APF, their processes are found in the larval-specific antennal lobe (A1, 2). Right columns of A1, 2 show a zoom-in of the dashed boxes. Green arrowhead in (A2) indicates robust dendrite re-extension of embryonic-born PNs across the developing antennal lobe at 6 hr APF. (A1): N=6; (A2): N=12; (A3): N=9; (A4): N=12; (A5): N=9; (A6): N=5. (B) Schematic of the sparse, stochastic, and dual-color labeling strategy. In this strategy, the same cell has one copy of UAS-responsive conditional reporter 1 and one copy of QUAS-responsive reporter 2, both of which are integrated into the same 86Fb genomic locus (i.e. UAS-FRT-stop-FRT-reporter1/QUAS-FRT-stop-FRT-reporter2). FLP expression yields cis and trans recombination of FRT sites in a stochastic manner. Upon GAL4 expression, reporter 1 is expressed in cells with cis recombination, whereas reporter 2 is expressed only when cis and trans recombination events co-occur. (C) Sparse labeling of lov+ PNs (labeled in green; single-cell lov+ PNs in gray) at indicated developmental stages. (C6) and (C7) are zoom-in images of the rectangular boxes in (C2) and (C3), respectively. Arrowheads indicate nascent, adult-specific dendrites. Larval-specific dendrites are outlined by dashed orange lines. Arrows indicate axons projecting towards high brain centers. (C1): N=6; (C2–3): N=6; (C4): N=4; (C5): N=4. (D) Two-photon time-lapse imaging of a single embryonic-born PN (Split7+; pseudo-colored in yellow) in a brain dissected at 3 hr APF and cultured for 23 hr ex vivo. Arrowhead in (D3) denote the thickening of the main process. Arrowheads in D4, 5 denote dendritic protrusions dorsal to larval-specific dendrites. (D9) shows neurite tracing of the embryonic-born PN. Triangles in (D9) indicate the degenerating larval-specific dendrites. N=3. (E) Schematic summary of remodeling of embryonic-born PN dendrites. Following simultaneous pruning and re-extension, embryonic-born PNs timely integrate into an adult olfactory circuit and, together with larval-born PNs, participate in the prototypic map formation.

To characterize dendritic re-extension at single-cell resolution, we developed a sparse, stochastic labeling strategy to label single lov+ PNs (Figure 8B). We found that lov+ PNs produced nascent branches from the main process dorsal to larval-specific dendrites as early as 3 hr APF (Figure 8C2–3; arrowheads in Figure 8C6–7). At 6 hr APF, when larval-specific dendrites were completely segregated from lov+ PNs, the robust extension of adult-specific dendrites was seen across the developing antennal lobe (Figure 8C4). These data indicate that lov+ PNs re-extend their adult-specific dendrites at a more dorsal location before the larval-specific dendrites are completely pruned.

Do other embryonic-born PNs prune and re-extend their dendrites simultaneously? Like lov drivers, Mz612-GAL4 labels embryonic-born PNs, one of which is VA6 PN (Marin et al., 2005). In 3 hr APF brains co-labeled for Mz612+ and lov+ PNs, we could unambiguously access three single embryonic-born PN types: (1) lov+ Mz612– PN, (2) lov– Mz612+ PN, and (3) lov+ Mz612+PN (Figure 8—figure supplement 2A–B). Tracing of individual dendritic branches showed that all these PNs already re-extended dendrites to varying extents prior to the separation of larval-specific dendrites from the rest of the processes (Figure 8—figure supplement 2C). Thus, concurrent pruning and re-extension apply to multiple embryonic-born PN types.

To capture the remodeling at the higher temporal resolution, we performed two-photon time-lapse imaging of single embryonic-born PNs labeled by Split7-GAL4 (Figure 8D, Figure 8—video 2, Figure 8—figure supplement 3). This GAL4 labels one embryonic-born PN (either VA6 or VA2 PN) at early pupal stages but eight PN types at 24 hr APF (Xie et al., 2021). Initially (3 hr APF + 0 hr ex vivo), no adult-specific dendrites were detected in live Split7+ PNs (Figure 8D1). The following ~3 hr ex vivo saw thickening of the main process (arrowhead in Figure 8D3). From 4 hr ex vivo onwards, re-extension occurred in the presumed developing antennal lobe located dorsal to larval-specific dendrites (arrowheads in Figure 8D4–8; see traces in Figure 8D9). Live imaging of Split7+ PNs also revealed that fragmentation of larval-specific dendrites occurred at the distal ends (Figure 8—figure supplement 3B1–5), and the process leading to larval-specific dendrites gradually disappeared as pruning approached completion (Figure 8—figure supplement 3B6–10). These observations suggest that pruning of embryonic-born PN dendrites is not initiated by severing at the proximal end. Distal-to-proximal pruning, rather than in the reversed direction, further supports concurrent but spatially segregated pruning and re-extension processes.

It has been shown that dendritic pruning of embryonic-born PNs requires ecdysone signaling in a cell-autonomous manner (Marin et al., 2005). We asked if the re-extension process also depends on ecdysone signaling. We expressed a dominant negative form of ecdysone receptor (EcR-DN) in most PNs (including lov+ PNs) and monitored the development of lov+ PN dendrites (Figure 8—figure supplement 4). We found that inhibition of ecdysone signaling by EcR-DN expression not only suppressed pruning, but also blocked re-extension. This is consistent with a previous study reporting the dual requirement of ecdysone signaling in the pruning and re-extension of Drosophila anterior paired lateral (APL) neurons, although, unlike embryonic-born PNs, APL neurons prune and re-extend processes sequentially (at 6 hr and 18 hr APF, respectively) (Mayseless et al., 2018). We currently could not distinguish if the lack of re-extension is due to defective pruning, or if ecdysone signaling controls pruning and re-extension independently.

Taken together, our data demonstrate that embryonic-born PNs prune and re-extend dendrites simultaneously at spatially distinct regions, and that both processes require ecdysone signaling (Figure 8E). Such a ‘multi-tasking’ ability explains how embryonic-born PNs can re-integrate into the adult olfactory circuit and engage in its prototypic map formation in a timely manner.

Discussion

Wiring logic for the prototypic olfactory map

Prior to this study, no apparent logic linking PN lineage, birth order, and adult glomerular position has been found. Our systematic analyses of dendritic patterning at the resolution of specific PN types across development identified wiring logic underlying the spatial organization of the prototypic olfactory map (Figures 3 and 4).

We found that PNs of a given lineage and temporal cohort share similar dendrite targeting specificity and timing. Notably, dendrites of adPNs and lPNs respectively pattern the antennal lobe in rotating and binary manners following birth order. Based on our new observations and previous findings, we discuss possible mechanisms that execute the wiring logic to form the initial map: (1) specification of the initial dendrite targeting through combinatorial inputs from lineage and birth order, (2) PN dendrite-dendrite interactions, and (3) contribution of the degenerating larval-specific antennal lobe.

The spatial distinctions of cell bodies (e.g. Figure 1D1), axons (e.g. Figure 1—figure supplement 2A), and dendrites (e.g. Figure 4A1) of adPNs and lPNs observed in 0 hr APF pupal brain suggest that lineage endows projection specificity very early on. Lineage-specific transcription factors have been identified to instruct PN neurite targeting (Komiyama et al., 2003; Komiyama and Luo, 2007; Li et al., 2017; Xie et al., 2022), which might explain the differences between the adPN and lPN dendritic maps. Nonetheless, lineage alone does not account for the characteristic dendritic patterns. Rather, dendrite targeting can be predicted using combinatorial inputs from lineage and birth order. This combinatorial strategy is also seen in neuronal fate diversification and wiring of the Drosophila optic lobe and ventral nerve cord (Erclik et al., 2017; Mark et al., 2021), suggesting that it is a general principle in wiring the fly brain and likely also used in vertebrates (Holguera and Desplan, 2018; Sen, 2023). Substantial advances have been made in understanding how temporal patterning arises for intra-lineage specification (Doe, 2017; Miyares and Lee, 2019). For instance, the embryonic ventral nerve cord neuroblasts sequentially express a cascade of temporal transcription factors (TTFs) to specify temporal identity (Isshiki et al., 2001). Larval optic lobe neuroblasts also deploy the same strategy but use a completely different TTF cascade (Li et al., 2013). Earlier studies show Chinmo, a TTF, and RNA-binding proteins that regulate Chinmo translation, control neuronal cell fate of the adPN lineage (Zhu et al., 2006; Liu et al., 2015). Specifically, DL1 PNs mutant for Chinmo project dendrites to D glomerulus that is targeted by the fourth larval-born adPNs (Zhu et al., 2006), demonstrating temporal order specifies final glomerular targeting. However, whether approximate temporal cohorts of a given PN lineage we described arise from sequential expression of temporal factors, and how such factors translate into initial dendrite patterning remains a fertile ground for future studies.

Our time-lapse imaging data reveals robust PN dendritic dynamics during the initial targeting process (Figures 58), suggesting that cellular interactions among PN dendrites contribute to the initial map formation. This appears to contrast with the PN-ORN map in the mature antennal lobe, which is highly stable; connection specificity remains largely unchanged upon genetic ablation of their synaptic partners (Berdnik et al., 2006). Future works using early-onset genetic drivers for specific PN types for ablation can be used to investigate interactions between different PN groups, such as adPNs and lPNs, in the construction of the initial PN dendrite map.

Does the degenerating larval-specific antennal lobe contribute to the initial dendrite patterning of the developing adult-specific antennal lobe? Earlier studies found that the larval-specific ORN axons secrete semaphorins, Sema-2a and Sema-2b, which act as repulsive ligands for dendrites of Sema-1a-expressing PNs (including DL1 PNs) (Komiyama et al., 2007; Sweeney et al., 2011). As the larval-specific lobe is located ventromedial to the adult-specific lobe, Sema-2a/b and Sema-1a form opposing gradients along the dorsolateral-ventromedial axis. When DL1 PNs (the first-born/developed) begin to target their dendrites, this repulsive action could destabilize branches in the ventromedial direction and thus favor dorsolateral targeting. This provides a plausible explanation as to why the adPN rotation pattern begins at the dorsolateral position. It would be interesting to see if the pattern is perturbed upon ablation of larval-specific ORNs.

Our new tools for labeling and genetic manipulation of distinct PN types (Figure 2) will now enable in-depth investigations into the potential cellular interactions and molecular mechanisms leading to the initial map organization.

Wiring logic evolves as development proceeds

After the initial map formation at 12 hr APF, dendrite positions in the antennal lobe could change substantially in the next 36 hr (for example, see DC2 PNs in Figure 3B46 and DA1 and VA1d/DC3 PNs in Figure 3C47). These changes occur when dendrites of PNs with neighboring birth order begin to segregate and when ORN axons begin to invade the antennal lobe. Accordingly, the ovoid-shaped antennal lobe turns into a globular shape (30–50 hr APF; Figure 3C6-7). These PN-autonomous and non-autonomous changes likely mask the initial wiring logic, explaining why previous studies, which mostly focused on examining the final glomerular targets in adults (Jefferis et al., 2001), have missed the earlier organization. Interestingly, the process of PN dendritic segregation coincides with the peak of PN transcriptomic diversity at 24 hr APF (Li et al., 2017; Xie et al., 2021).

Recent proteomics and genetic analyses have indicated that PN dendrite targeting is mediated by cell-surface proteins cooperating as a combinatorial code (Xie et al., 2022). The evolving wiring logic, which is consistent with the stepwise assembly of an olfactory circuit (Hong and Luo, 2014), suggests the combinatorial codes are not static. We propose that PNs use a numerically simpler code for initial dendrite targeting. Following the expansion of transcriptomic diversity, PNs acquire a more complex code mediating dendritic segregation of neighboring PNs and matching of PN dendrites and ORN axons. Functional characterization of differentially expressed genes between 12 hr and 24 hr APF PNs may provide molecular insights into how the degree of discreteness in the olfactory map arises.

Although the initial wiring logic is not apparent in the final map, several lines of evidence suggest the final map depends on the initial map. First, as mentioned above, the change of the temporal identity of DL1 PNs affects glomerular targeting (Zhu et al., 2006). Second, loss of Sema-1a in DL1 PNs occasionally causes mistargeting in areas outside of the antennal lobe, and dendrite mistargeting phenotype along the dorsolateral-ventromedial axis is persistent across development as well as in adulthood (Komiyama et al., 2007). Our work thus demonstrates that identification of the wiring logic in the early stages should help us better resolve the architectures in complex neural circuits.

Selective branch stabilization as a cellular mechanism for dendrite targeting

Utilizing an early pupal brain explant culture system coupled with two-photon and AO-LLSM imaging (Figure 5), we presented the first time-lapse videos following dendrite development of a specific PN type – DL1 PNs (Figures 6 and 7). We found that DL1 PN dendrites initiate active targeting towards their dorsolateral target with direction-dependent branch stabilization. This directional selectivity provides a cellular basis for the emerging targeting specificity of PN dendrites at the beginning of olfactory map formation.

Although selective branch stabilization as a mechanism to achieve axon targeting specificity has been described in neurons in the vertebrate and invertebrate systems (e.g. Yates et al., 2001; Li et al., 2021), our time-lapse imaging showed, for the first time to our knowledge, that selective branch stabilization is also used to achieve dendrite targeting specificity. Furthermore, AO-LLSM imaging revealed that selective stabilization and destabilization of dendritic branches occur on the timescale of seconds. As the rate of olfactory circuit development in the brain explants was slower than normal development (Figure 5F), we might have captured PN dendritic dynamics in slow motion. Using AO-LLSM for high spatiotemporal resolution imaging, we just begin to appreciate how fast PN dendrites are coordinating trajectory choices with branch stabilization to make the appropriate decision. Having characterized the dendritic branch dynamics of the wild-type DL1 PNs, we have set the stage for future studies addressing how positional cues and the downstream signaling instruct wiring, and whether other PN types follow similar rules as DL1 PNs.

Simultaneous pruning and re-extension as novel remodeling mechanism for neuronal remodeling

Our data on embryonic-born adPN dendrite development reveals a novel mode of neuronal remodeling during metamorphosis (Figure 8). In mushroom body γ neurons and body wall somatosensory neurons, two well-characterized systems, larval-specific neurites are first pruned, followed by re-extension of adult-specific processes (Watts et al., 2003; Williams and Truman, 2005; Yaniv and Schuldiner, 2016). However, embryonic-born adPNs prune larval-specific dendrites and re-extend adult-specific dendrites simultaneously but at spatially separated subcellular compartments. Such spatial segregation suggests that regional external cues could elicit compartmentalized downstream signals leading to opposite effects on the dendrites. Subcellular compartmentalization of signaling and cytoskeletal organization has been observed in diverse neuron types across species (Rolls et al., 2007; Kanamori et al., 2013; O’Hare et al., 2022).

Why do embryonic-born adPNs ‘rush’ to re-extend dendrites? During normal development, it takes at least 18 hr for embryonic-born adPNs to produce and properly target dendrites (growth at 3–6 hr APF, initial targeting at 6–12 hr APF, and segregation at 21–30 hr APF). Given that the dendritic re-extension of embryonic-born PNs is ecdysone dependent (Figure 8—figure supplement 4), if the PNs did not re-extend dendrites at 3 hr APF, they would have to wait for the next ecdysone surge at ~20 hr APF (Thummel, 2001), which might be too late for their dendrites to engage in the prototypic map formation. Thus, embryonic-born PNs develop a remodeling strategy that coordinates with the timing of systemic ecdysone release. By simultaneous pruning and re-extension, embryonic-born adPNs timely re-integrate into the adult prototypic map that readily serves as a target for subsequent ORN axon innervation.

In conclusion, our study highlights the power and necessity of type-specific neuronal access and time-lapse imaging to identify wiring logic and mechanisms underlying the origin of an olfactory map. Applying similar approaches to other developing neural maps across species should broaden our understanding of the generic and specialized designs that give rise to functional maps with diverse architectures.

Materials and methods

Drosophila stocks and husbandry

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Flies were maintained on a standard cornmeal medium at 25 °C. Fly lines used in this study included GH146-FLP (Hong et al., 2009), QUAS-FRT-stop-FRT-mCD8-GFP (Potter et al., 2010), UAS-mCD8-GFP (Lee and Luo, 1999), UAS-mCD8-FRT-GFP-FRT-RFP (Stork et al., 2014), VT033006-GAL4 (Tirian and Dickson, 2017), Mz19-GAL4 (Jefferis et al., 2004), 91G04-GAL4 (Jenett et al., 2012), Mz612-GAL4 (Marin et al., 2005), 71B05-GAL4 (Jenett et al., 2012), Split7-GAL4 (Xie et al., 2021), QUAS-FLP (Potter et al., 2010), and UAS-EcR.B1-ΔC655.F645A (Cherbas et al., 2003). The following GAL4 lines were obtained from Bloomington Drosophila Stock Center (BDSC): tsh-GAL4 (BDSC #3040) and lov-GAL4 (BDSC #3737).

The following two stocks were used for MARCM analyses: (1) UAS-mCD8-GFP, hs-FLP; FRTG13, tub-GAL80;; GH146-GAL4, and (2) FRTG13, UAS-mCD8-GFP (Lee and Luo, 1999).

The following lines were generated in this study: UAS-FRT10-stop-FRT10-3xHalo7-CAAX (on either II or III chromosome), UAS-FRT-myr-4xSNAPf-FRT-3xHalo7-CAAX (III), UAS-FRT-myr-mGreenLantern-FRT-3xHalo7-CAAX (II), QUAS-FRT-stop-FRT-myr-4xSNAPf (III), run-T2A-FLP (X), acj6-T2A-FLP (X), acj6-T2A-QF2 (X), CG14322-T2A-QF2 (III), and lov-T2A-QF2 (II).

Drosophila genotypes

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MARCM clonal analyses

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MARCM clonal analyses have been previously described (Lee and Luo, 1999). Larvae of the genotype UAS-mCD8-GFP, hs-FLP/+; FRTG13, tub-GAL80/FRTG13, UAS-mCD8-GFP;; GH146-GAL4/+ were heat shocked at 37 °C for 1 hr. To label the first-born DL1 PNs, heat shock was applied at 0–24 hr after larval hatching (ALH). MARCM clones of early, middle (mid-late for adPNs), and late larval-born PNs were generated by applying heat shocks at 42–48 hr, 66–72 hr, and 96–100 hr ALH, respectively. As larvae developed at different rates (Tennessen and Thummel, 2011), we reasoned that even if we could collect 0 hr–2 hr ALH larvae, their development might have varied by the time of heat shock. To minimize the effects of unsynchronized development, we selected those heat-shocked larvae that were among the first to form puparia and collected these white pupae in a ~3 hr window for the clonal analyses.

Transcriptomic analyses

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Transcriptomic analyses have been described previously (Xie et al., 2021). tSNE plots and dot plots were generated in Python using PN single-cell RNA sequencing data and code available at https://github.com/Qijing-Xie/FlyPN_development (Xie, 2021).

Generation of T2A-QF2/FLP lines

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To generate a T2A-QF2/FLP donor vector for acj6 (we used the same strategy for run, CG14322 and lov), a ~2000 bp genomic sequence flanking the stop codon of acj6 was PCR amplified and introduced into pCR-Blunt II-TOPO (ThermoFisher Scientific #450245), forming pTOPO-acj6. To build pTopo-acj6-T2A-QF2, T2A-QF2 including loxP-flanked 3xP3-RFP was PCR amplified from pBPGUw-HACK-QF2 (Addgene #80276), followed by insertion into pTOPO-acj6 right before the stop codon of acj6 by DNA assembly (New England BioLabs #E2621S). To generate T2A-FLP, we PCR-amplified FLP from the genomic DNA of GH146-FLP strain. QF2 in pTopo-acj6-T2A-QF2 was then replaced by FLP through DNA assembly. Using CRISPR Optimal Target Finder (Gratz et al., 2014), we selected a 20 bp gRNA target sequence that flanked the stop codon and cloned it into pU6-BbsI-chiRNA (Addgene #45946). If the gRNA sequence did not flank the stop codon, silent mutations were introduced at the PAM site of the donor vector by site-directed mutagenesis. Donor and gRNA vectors were co-injected into Cas9 embryos in-house or through BestGene.

Generation of FLP-out reporters

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To generate pUAS-FRT10-stop-FRT10-3xHalo7-CAAX, FRT10-stop-FRT10 was PCR amplified from pUAS-FRT10-stop-FRT10-mCD8-GFP (Li et al., 2021) and inserted into pUAS-3xHalo7-CAAX (Addgene #87646) through NotI and DNA assembly.

To generate pUAS-FRT-myr-4xSNAPf-FRT-3xHalo7-CAAX, we first PCR amplified myr-4xSNAPf from pUAS-myr-4xSNAPf (Addgene #87637) using FRT-containing primers. FRT-myr-4xSNAPf-FRT was then introduced into pCR-Blunt II-TOPO, forming pTOPO-FRT-myr-4xSNAPf-FRT. Using NotI-containing primers, FRT-myr-4xSNAPf-FRT was PCR amplified and subcloned into pUAS-3xHalo7-CAAX through NotI.

To generate pUAS-FRT-myr-mGreenLantern-FRT-3xHalo7-CAAX, we first PCR amplified mGreenLantern from pcDNA3.1-mGreenLantern (Addgene #161912). Using MluI and XbaI, we replaced 4xSNAPf in pUAS-myr-4xSNAPf with mGreenLantern to build pUAS-myr-mGreenLantern. myr-mGreenLantern was PCR amplified with the introduction of FRT sequence, followed by insertion into pCR-Blunt II-TOPO. Using the NotI-containing primers, FRT-myr-mGreenLantern-FRT was PCR amplified and subcloned into pUAS-3xHalo7-CAAX through NotI.

To generate pQUAS-FRT-stop-FRT-myr-4xSNAPf, we first PCR amplified FRT-stop from pJFRC7-20XUAS-FRT-stop-FRT-mCD8-GFP (Li et al., 2021) and inserted it into pTOPO-FRT-myr-4xSNAPf-FRT through DNA assembly to form pTOPO-FRT-stop-FRT-myr-4xSNAPf-FRT. Using NotI-containing forward and KpnI-containing reverse primers, FRT-stop-FRT-myr-4xSNAPf was PCR amplified and subcloned into p10XQUAST. p10XQUAST was generated using p5XQUAS (Addgene #24349) and p10xQUAS-CsChrimson (Addgene #163629).

attP24 and 86Fb landing sites were used for site-directed integration.

Immunofluorescence staining and confocal imaging

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Fly brain dissection for immunostaining and live imaging has been described (Wu and Luo, 2006). Briefly, brains were dissected in phosphate-buffered saline (PBS) and fixed with 4% paraformaldehyde in PBS for 20 min on a nutator at room temperature. Fixed brains were washed with 0.1% Triton X-100 in PBS (PBST) for 10 min twice. After blocking with 5% normal donkey serum in PBST for 1 hr at room temperature, the brains were incubated with primary antibodies overnight at 4 °C. After PBST wash, brains were incubated with secondary antibodies (1:1000; Jackson ImmunoResearch) in dark for 2 hr at room temperature. Washed and mounted brains were imaged with confocal laser scanning microscopy (ZEISS LSM 780; LSM 900 with Airyscan 2). Images were processed with ImageJ. Neurite tracing images were generated using Simple Neurite Tracer (SNT) (Arshadi et al., 2021). Primary antibodies used included chicken anti-GFP (1:1000; Aves Lab #GFP-1020), rabbit anti-DsRed (1:500; TaKaRa #632496), rat anti-Cadherin DN (1:30; Developmental Studies Hybridoma Bank DSHB DN-Ex#8 supernatant), and mouse anti-Bruchpilot (1:30; DSHB nc82 supernatant).

Chemical labeling

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Chemical labeling of Drosophila brains has been described (Kohl et al., 2014). Janelia Fluor (JF) Halo and SNAP ligands (stocks at 1 mM) were gifts from Dr. Luke Lavis (Grimm et al., 2017; Grimm et al., 2021).

Fixed brains were washed with PBST for 5 min, followed by incubation with Halo and/or SNAP ligands (diluted in PBS) for 45 min at room temperature. Brains were then washed with PBST for 5 min, followed by blocking and immunostaining if necessary. For the co-incubation of Halo and SNAP ligands, JF503-cpSNAP (1:1000) and JF646-Halo (1:1000) were used. Alternatively, JFX650-SNAP (1:1000) and JFX554-Halo (1:10,000) were used. When only Halo ligands were needed, either JF646-Halo or JF635-Halo (1:1000) was used.

For live brain imaging, dissected brains were incubated with Halo ligands diluted in culture media (described below) for 30 min at room temperature. For two-photon imaging, JF570-Halo was used at 1:5000. For AO-LLSM imaging, following JF646-Halo incubation at 1:1000, the brains were incubated with 1 µM Sulforhodamine 101 (Sigma) for 5 min at room temperature. The brains were then briefly washed with culture media before imaging.

Brain explant culture setup and medium preparation

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Brain explant culture setup was modified based on Li et al., 2021; Li and Luo, 2021. A Sylgard plate with a thickness of ~2 millimeters was prepared by mixing base and curing agent at 10:1 ratio (DOW SYLGARD 184 Silicone Elastomer Kit). The mixture was poured into a 60 mm × 15 mm dish in which it was cured for two days at room temperature. Once cured, the plate was cut into small squares (~15 mm × ~15 mm). Indentations were created based on the size of an early pupal brain using a No.11 scalpel. Additional slits were made around the indentations for attaching imaginal discs which served as anchors to hold the brain position. A square Sylgard piece was then placed in a 60 mm × 15 mm dish or on a 25 mm round coverslip in preparation for two-photon/AO-LLSM imaging.

Culture medium was prepared based on published methods (Rabinovich et al., 2015; Li and Luo, 2021; Li et al., 2021). The medium contained Schneider’s Drosophila Medium (ThermoFisher Scientific #21720001), 10% heat-inactivated Fetal Bovine Serum (ThermoFisher Scientific #16140071), 10 µg/mL human recombinant insulin (ThermoFisher Scientific #12585014; stock = 4 mg/mL), 1:100 Penicillin-Streptomycin (ThermoFisher Scientific #15140122). For 0 hr–6 hr APF brain culture, 0.5 mM ascorbic acid (Sigma #A4544; stock concentration = 50 mg/mL in water) was included. 20-hydroxyecdysone (Sigma #H5142; stock concentration = 1 mg/mL in ethanol) was used for 0 hr–6 hr and 12 hr brain explants at 20 µM and 2 µM, respectively. Culture medium was oxygenated for 20 min before use.

Single- and dual-color imaging with two-photon microscopy

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Single- and dual-color imaging of PNs were performed at room temperature using a custom-built two-photon microscope (Prairie Technologies) with a Chameleon Ti:Sapphire laser (Coherent) and a 16 X water-immersion objective (0.8 NA; Nikon). Excitation wavelength was set at 920 nm for GFP imaging, and at 935 nm for co-imaging of mGreenLantern and JF570-Halo. z-stacks were obtained at 4 µm increments (10 µm increments for Figure 5—video 1). Images were acquired at a resolution of 1024 × 1024 pixel2 (512 × 512 for Figure 5—video 1), with a pixel dwell time of 6.8 µs and an optical zoom of 2.1, and at a frequency every 20 min for 8–23 hr.

Dual-color imaging with AO-LLSM

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For AO-LLSM-based imaging, the excitation and detection objectives along with the 25 mm coverslip were immersed in ~40 mL of culture medium at room temperature. Explant brains held on Sylgard plate were excited simultaneously using 488 nm (for GFP) and 642 nm (for JF-646) lasers operating with ~2–10 mW input power to the microscope (corresponding to ~10–50 µW at the back aperture of the excitation objective). An exposure time of 20–50 msec was used to balance imaging speed and signal-to-noise ratio (SNR). Dithered lattice light-sheet patterns with an inner/outer numerical aperture of 0.35/0.4 or 0.38/0.4 were used. The optical sections were collected by an axial step size of 250 nm in the detection objective coordinate, with a total of 81–201 steps (corresponding to a total axial scan range of 20–50 µm). Emission light from GFP and JF-646 was separated by a dichromatic mirror (Di03-R561, Semrock, IDEX Health & Science, LLC, Rochester, NY) and captured by two Hamamatsu ORCA-Fusion sCMOS cameras simultaneously (Hamamatsu Photonics, Hamamatsu City, Japan). Prior to the acquisition of the time series data, the imaged volume was corrected for optical aberrations using a two-photon guide star-based adaptive optics method (Chen et al., 2014; Wang et al., 2014; Liu et al., 2018). Each imaged volume was deconvolved using Richardson-Lucy algorithm on HHMI Janelia Research Campus’ or Advanced Bioimaging Center’s computing cluster (https://github.com/scopetools/cudadecon, Lambert et al., 2023; https://github.com/abcucberkeley/LLSM3DTools, Ruan and Upadhyayula, 2020) with experimentally measured point spread functions obtained from 100 or 200 nm fluorescent beads (Invitrogen FluoSpheres Carboxylate-Modified Microspheres, 505/515 nm, F8803, FF8811). The AO-LLSM was operated using a custom LabVIEW software (National Instruments, Woburn, MA).

Statistics

For data analyses, t-test and one-way ANOVA were used to determine p values as indicated in the figure legend for each graph, and graphs were generated using Excel. Exact p values were provided in source data files.

Material and data availability

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All reagents generated in this study are available from the lead corresponding author upon request. Figure 3—figure supplement 3—source data 1, Figure 6—source data 1, and Figure 7—source data 1 contain the numerical and statistical data used to generate the figures. The confocal imaging dataset is available at Brain Image Library under DOI https://doi.org/10.35077/g.933.

Appendix 1

Appendix 1—key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
Genetic reagent (D. melanogaster)GH146-FLPDOI: 10.1038/nn.2442
Genetic reagent (D. melanogaster)QUAS-FRT-stop-FRT-mCD8-GFPDOI: 10.1016 /j.cell.2010.02.025
Genetic reagent (D. melanogaster)UAS-mCD8-GFPDOI: 10.1016 /s0896-6273(00)80701–1
Genetic reagent (D. melanogaster)UAS-mCD8-FRT-GFP-FRT-RFPDOI: 10.1016 /j.neuron.2014.06.026
Genetic reagent (D. melanogaster)VT033006-GAL4DOI: 10.1101/198648
Genetic reagent (D. melanogaster)Mz19-GAL4DOI: 10.1242/dev.00896
Genetic reagent (D. melanogaster)91 G04-GAL4DOI: 10.1016 /j.celrep.2012.09.011
Genetic reagent (D. melanogaster)Mz612-GAL4DOI: 10.1242/dev.01614
Genetic reagent (D. melanogaster)71B05-GAL4DOI: 10.1016 /j.celrep.2012.09.011
Genetic reagent (D. melanogaster)Split7-GAL4DOI: 10.7554/eLife.63450FlyLight:SS01867
Genetic reagent (D. melanogaster)QUAS-FLPDOI: 10.1016 /j.cell.2010.02.025
Genetic reagent (D. melanogaster)UAS-EcR.B1-ΔC655.F645ADOI: 10.1242/dev.00205
Genetic reagent (D. melanogaster)tsh-GAL4Bloomington Drosophila Stock CenterBDSC:3040
Genetic reagent (D. melanogaster)lov-GAL4Bloomington Drosophila Stock CenterBDSC:3737
Genetic reagent (D. melanogaster)UAS-mCD8-GFP, hs-FLP; FRTG13, tub-GAL80;; GH146-GAL4DOI: 10.1016 /s0896-6273(00)80701–1
Genetic reagent (D. melanogaster)FRTG13, UAS-mCD8-GFPDOI: 10.1016 /s0896-6273(00)80701–1
Genetic reagent (D. melanogaster)UAS-FRT10-stop-FRT10-3xHalo7-CAAXthis paperon either II or III chromosome; see Materials and methods
Genetic reagent (D. melanogaster)UAS-FRT-myr-4xSNAPf-FRT-3xHalo7-CAAXthis paperon III chromosome; see Materials and methods
Genetic reagent (D. melanogaster)UAS-FRT-myr-mGreenLantern-FRT-3xHalo7-CAAXthis paperon II chromosome; see Materials and methods
Genetic reagent (D. melanogaster)QUAS-FRT-stop-FRT-myr-4xSNAPfthis paperon III chromosome; see Materials and methods
Genetic reagent (D. melanogaster)run-T2A-FLPthis paperon X chromosome; see Materials and methods
Genetic reagent (D. melanogaster)acj6-T2A-FLPthis paperon X chromosome; see Materials and methods
Genetic reagent (D. melanogaster)acj6-T2A-QF2this paperon X chromosome; see Materials and methods
Genetic reagent (D. melanogaster)CG14322-T2A-QF2this paperon III chromosome; see Materials and methods
Genetic reagent (D. melanogaster)lov-T2A-QF2this paperon II chromosome; see Materials and methods
Antibodychicken polyclonal anti-GFPAves LabRRID:AB_10000240; Aves Lab:GFP-1020(1:1000)
Antibodyrabbit polyclonal anti-DsRedTaKaRaRRID:AB_10013483; TaKaRa:632496(1:500)
Antibodyrat monoclonal anti-Cadherin DNDevelopmental Studies Hybridoma BankRRID:AB_528121; DSHB:DN-Ex#8(1:30)
Antibodymouse monoclonal anti-BruchpilotDevelopmental Studies Hybridoma BankRRID:AB_2314866; DSHB:nc82 supernatant(1:30)
Recombinant DNA reagentpBPGUw-HACK-QF2AddgeneRRID:Addgene_80276
Recombinant DNA reagentpU6-BbsI-chiRNAAddgeneRRID:Addgene_45946
Recombinant DNA reagentpUAS-3xHalo7-CAAXAddgeneRRID:Addgene_87646
Recombinant DNA reagentpUAS-myr-4xSNAPfAddgeneRRID:Addgene_87637
Recombinant DNA reagentpcDNA3.1-mGreenLanternAddgeneRRID:Addgene_161912
Recombinant DNA reagentp5XQUASAddgeneRRID:Addgene_24349
Recombinant DNA reagentp10xQUAS-CsChrimsonAddgeneRRID:Addgene_163629
Recombinant DNA reagentpUAS-FRT10-stop-FRT10-3xHalo7-CAAXthis paperbackbone from pUAS-3xHalo7-CAAX; see Materials and methods
Recombinant DNA reagentpUAS-FRT-myr-4xSNAPf-FRT-3xHalo7-CAAXthis paperbackbone from pUAS-3xHalo7-CAAX; see Materials and methods
Recombinant DNA reagentpUAS-FRT-myr-mGreenLantern-FRT-3xHalo7-CAAXthis paperbackbone from pUAS-3xHalo7-CAAX; see Materials and methods
Recombinant DNA reagentpUAS-myr-mGreenLanternthis paperbackbone from pUAS-myr-4xSNAPf; see Materials and methods
Recombinant DNA reagentpQUAS-FRT-stop-FRT-myr-4xSNAPfthis paperbackbone from p5XQUAS; see Materials and methods
Chemical compound, drugSYLGARD 184 Silicone Elastomer KitDOWDOW:2646340
Chemical compound, drugSchneider’s Drosophila MediumThermoFisher ScientificThermoFisher Scientific:21720001
Chemical compound, drugFetal Bovine SerumThermoFisher ScientificThermoFisher Scientific:16140071used at 10%
Chemical compound, drugHuman recombinant insulinThermoFisher ScientificThermoFisher Scientific:12585014used at 10 µg/mL
Chemical compound, drugPenicillin-StreptomycinThermoFisher ScientificThermoFisher Scientific:15140122(1:100)
Chemical compound, drugAscorbic acidSigmaSigma:A4544used at 50 mg/mL in water
Chemical compound, drug20-hydroxyecdysoneSigmaSigma:H5142used at 20 µM and 2 µM
Chemical compound, drugJF503-cpSNAPDOI: 10.1038/nmeth.4403; DOI: 10.1021/jacsau.1c00006(1:1000); gift from Dr. Luke Lavis
Chemical compound, drugJF646-HaloDOI: 10.1038/nmeth.4403; DOI: 10.1021/jacsau.1c00006(1:1000); gift from Dr. Luke Lavis
Chemical compound, drugJFX650-SNAPDOI: 10.1038/nmeth.4403; DOI: 10.1021/jacsau.1c00006(1:1000); gift from Dr. Luke Lavis
Chemical compound, drugJFX554-HaloDOI: 10.1038/nmeth.4403; DOI: 10.1021/jacsau.1c00006(1:10000); gift from Dr. Luke Lavis
Chemical compound, drugJF635-HaloDOI: 10.1038/nmeth.4403; DOI: 10.1021/jacsau.1c00006(1:1000); gift from Dr. Luke Lavis
Chemical compound, drugJF570-HaloDOI: 10.1038/nmeth.4403; DOI: 10.1021/jacsau.1c00006(1:5000); gift from Dr. Luke Lavis
Chemical compound, drugSulforhodamine 101SigmaSigma:S7635used at 1 µM
Software, algorithmZENCarl ZeissRRID:SCR_013672
Software, algorithmImageJNational Institutes of HealthRRID:SCR_003070
Software, algorithmPython Programming LanguagePythonRRID:SCR_008394http://www.python.org/

Data availability

Figure 3—source data 1, Figure 5—source data 1, Figure 6—source data 1, and Figure 7—source data 1 contain the numerical and statistical data used to generate the figures. The confocal imaging dataset is available at Brain Image Library under DOI https://doi.org/10.35077/g.933.

The following data sets were generated
    1. Wong KLK
    (2023) Brain Image Library
    Origin of wiring specificity in an olfactory map revealed by neuron type-specific, time-lapse imaging of dendrite targeting: Confocal imaging of developing fly brain.
    https://doi.org/10.35077/g.933
The following previously published data sets were used

References

    1. Yaniv SP
    2. Schuldiner O
    (2016) A fly’s view of neuronal remodeling
    Wiley Interdisciplinary Reviews. Developmental Biology 5:618–635.
    https://doi.org/10.1002/wdev.241

Decision letter

  1. Sonia Sen
    Reviewing Editor; Tata Institute for Genetics and Society, India
  2. K VijayRaghavan
    Senior Editor; National Centre for Biological Sciences, Tata Institute of Fundamental Research, India
  3. Sonia Sen
    Reviewer; Tata Institute for Genetics and Society, India

Our editorial process produces two outputs: (i) public reviews designed to be posted alongside the preprint for the benefit of readers; (ii) feedback on the manuscript for the authors, including requests for revisions, shown below. We also include an acceptance summary that explains what the editors found interesting or important about the work.

Decision letter after peer review:

Thank you for submitting your article "Origin of wiring specificity in an olfactory map: dendrite targeting of projection neurons" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, including Sonia Sen as Reviewer #1 and Reviewing Editor, and the evaluation has been overseen by K VijayRaghavan as the Senior Editor.

The reviewers have discussed their reviews with one another, and the Reviewing Editor has drafted this to help you prepare a revised submission.

Essential revisions:

1. Quantifications: While the data are qualitatively convincing, could the authors please quantify their observations and mention the sample size for each of their experiments? It would be useful to have a way of describing the variability between brains.

2. The time windows: could the authors please define their time windows better, particularly in the context of other neurons that are born? (Please see detailed comments below)

3. Writing: Could the authors please place their work in the broader context of the literature on how temporal patterning translates to dendritic patterning? While doing so, could they also place it in the framework of formal possibilities of how this might occur?

4. Since the antennal lobe is a 3D structre, we would like the authors represent their 2D models as 3D? (Does their model hold up?)

We also suggest that the authors experimentally test their prediction. This could be by showing that a later-born neuron from adPN lineage will always target further clockwise. Or they could use Chinmo to change the temporal identity of the neurons. (Or any similar experiment they choose). If not, we suggest that they revisit their text to tone down their claim of dendrites targeting according to birth order.

Aside from these essential revisions, please read the detailed reviews below and address them whenever possible.

Reviewer #1 (Recommendations for the authors):

I appreciate the quality and extent of the work presented in this manuscript and have only comments related to its presentation.

1. I find great value in describing how the earliest events in the birth of the neuron – through temporal patterning – translate to its target specification. This is an important area in neurodevelopment and one into which inroads have been made in the recent past. Much of this work has been in the ventral nerve cord and the optic lobe. It would benefit this manuscript immensely to place their work within this context.

2. The manner in which the study is currently presented gives the (false) impression that this is 'merely' a descriptive study that conveys in more detail an already known phenomenon. This is likely because the authors have restricted their reference to literature on the antennal lobe. The authors should present this work in the framework of formal possibilities of how birth order might affect targeting. Currently, the articulation of the problem they are addressing is too generic.

Reviewer #2 (Recommendations for the authors):

Wong et al. used very sophisticated genetics to perform a thorough investigation of adPN and lPN lineages across various developmental stages to find out how dendrites segregate into discrete glomeruli during development. The endeavours devoted to data collection are very impressive. The data are convincing and adequately interpreted.

The studies are thorough. With the limitation of genetic tools available, Wong et al. are still able to achieve a comprehensive study of two neuronal lineages to extract wiring logic.

Ex vivo explant time-lapse imaging provides details of how dendritic neurites behave during development, which could not be reached with conventional standard fixation-staining protocols. I agreed with their words that '…the (power and) necessity of type-specific neuronal access and time-lase imaging in identifying wiring mechanisms…'. The methodology will become a paradigm in the field.

I have some specific comments for the authors:

1. Adult-specific antennal lobes were first built outside the larval antennal lobe and then took over the larval antennal lobe territory. They also observed that embryonic-born PNs retracted and extended dendrites simultaneously at spatially distinct regions. It was unexplained and undiscussed if the larval antennal lobes had a footprint left at that region to influence larval-born PN dendritic targeting, such as glial cells, unpruned dendrites, or presynaptic partners. And it remains to be addressed whether the rotation of initial dendritic targeting of PNs is related to the remnants of larval-specific antennal lobes.

2. Unlike the anterodorsal lineage that generates monoglomerulous PNs continuously, the lateral lineage intermingles the birth of monoglomerulous PNs (studied in this manuscript) and antennal mechanosensory and motor center (AMMC) PNs during neurogenesis (Lin et al., 2012, PLoS Biology). While it is convincing adPNs born around the same time form a cohort to target dendrites to similar territory, it is unclear if those AMMC PNs which are born between monoglomerulous PNs form a cohort with those PNs and target their dendrites to similar territory. Besides, more lPNs (7) than adPNs (3) were categorized as 'early-born', and I was wondering if those 'early-born' lPNs can be further partitioned into smaller cohorts if AMMC PNs are considered.

3. The authors proposed a compelling model about how PNs chose initial dendritic targeting territory based on its lineage and birth timing and showed a clock-like rotation as the targeting pattern. However, the antennal lobe is actually a 3D structure. 2D projection looks very intriguing, but it does not really reflect how targeting territory is selected in a 3D space. It might be more accurate to revise it as a 3D model.

4. The definition of 'early', 'middle', and 'late' born PNs from both lineages is not very clear. Based on birth timing (what interval?) or dendrite targeting? Why anterodorsal lineage has fewer early-born PNs than the lateral lineage (3 vs. 7)?

5. In this manuscript, many neurons from the lateral lineage were left undiscussed. It might be good to remind readers that this manuscript is focusing on the monoglomerulous PNs only; interneurons and other types of PNs from the lateral lineage won't be discussed in the current work.

Reviewer #3 (Recommendations for the authors):

I find the paper a strong candidate for eLife. The genetics is exceptional and the effort to comprehensively dissect the targeting of as many projection neurons as possible is both impressive and commendable. The ex-vivo time-lapse imaging is likewise super-impressive.

A few points that should be strengthened in my opinion:

1) Most of the figures represent convincing qualitative information without giving us any quantitative measures. At a very minimum, I would like to know how many neurons or brains (or both) were images and gave a consistent finding. Even better would be to find ways to describe the variability between brains. I understand that the lack of a "standard brain" for these developmental stages makes this more complicated but perhaps a course resolution would do.

2) I am not convinced by the statement that "groups" of neurons (grouped by birth date) target their dendrites to the same location. There are even a few projection neurons that belong to two groups – what does this mean? The clockwise rotation model should, in principle, offer a way to test this – no? It predicts that regardless of the stage, always the next-born neuron should target the clockwise correct location compared to the previous. This should strengthen the statement and verify if indeed there are groups – of indistinguishable (at this stage) dendrites…

3) While I don't necessarily think that every paper needs to include mechanistic experiments, the two-step model presented in this manuscript, coupled with the many dendrite-targeting mutants that the Luo lab has previously generated, really makes it compelling to check if they are required for the initial targeting or later refinement. So for example, is the initial age and lineage dependent targeting normal in Sema1a; Ten-a/m; etc… Of course – does the final targeting depend on correct initial targeting. This is not absolutely necessary but adding some mechanistic aspects would make the study much more compelling to me.

4) If I understand correctly, previous data from the Luo lab has shown that the ORN-PN map is extremely stable, even if you kill or inactivate specific ORN/PNs. In light of this new study, PN-PN interactions have the potential to be important. Could adPNs affect the targeting of lPNs? Or vice versa? If this was not tested before, then perhaps even just discussing the option, rather than doing the experiments, seems like a logical step to me.

https://doi.org/10.7554/eLife.85521.sa1

Author response

Essential revisions:

1. Quantifications: While the data are qualitatively convincing, could the authors please quantify their observations and mention the sample size for each of their experiments? It would be useful to have a way of describing the variability between brains.

Thank you for pointing out the need of quantification. Sample size for each experiment in Figures 6 and 7 has already been provided during the initial submission of the manuscript. We now include the sample size for experiments in Figures 1, 3, 4, 5 and 8. This information can be found in the figure legends.

We reason that the variability among sample brains could arise from biological (e.g., developmental rates, cell number of each neuronal type, and cell body positions) and technical variations (e.g., brain mounting, staining efficiency, genetic design). We now include a supplemental table describing the variations we observed, and what measures we have taken to minimize them, if possible (Supplementary file 1).

We had once considered providing additional samples for each genotype (just like what we did for the MARCM experiments; Figure 3D4–9, Figure 3 —figure supplement 3B–E, Figure 4B). However, we observed very stereotyped dendrite targeting of a given PN across development (see DL1 PNs as an example in Figure 3A3, 3D1–3), and presentation of all data comprising various genotypes and developmental stages would be overwhelming for readers. In the main figures, we present the most representative images selected from reproducible dataset so that readers can focus on the wiring logic that organizes different types of PNs into a neural circuit. To help researchers interact directly with our imaging data, we are in the process of depositing raw confocal images into Brain Image Library (https://www.brainimagelibrary.org/). Relevant links will be provided when available. This should allow one to examine the dendrite patterning of specific PN types at developmental stages of interest, stack-by-stack or at any angle, and to examine the variability among individual samples.

2. The time windows: could the authors please define their time windows better, particularly in the context of other neurons that are born? (Please see detailed comments below)

We now add text to describe how we define the approximate temporal cohorts of PNs and include the time intervals during which we applied the 1-hour heat shock to generate single-cell MARCM clones. Please see details in our response to Comment #4 from Reviewer #2.

3. Writing: Could the authors please place their work in the broader context of the literature on how temporal patterning translates to dendritic patterning? While doing so, could they also place it in the framework of formal possibilities of how this might occur?

We totally agree with Editors and Reviewers that there is a rich literature on the temporal patterning of the ventral nerve cord and optic lobe neuroblasts, and the discoveries of the temporal transcription factor cascades are remarkable (e.g., Doe, 2017; Miyares and Lee, 2019). In the antennal lobe, Chinmo, a temporal transcription factor, and the temporal gradients of RNAbinding proteins that regulate Chinmo translation, have been shown to govern adPN cell fate (Zhu et al., 2006; Liu et al., 2015). From these studies, it is tempting to speculate that the approximate temporal cohorts of a given PN lineage could be the result of differential expression of temporal factors. Future studies investigating the molecular signatures of these cohorts should inform us how PNs of a given lineage translate birth order into dendrite patterning.

We have placed our work in broader context and discussed the potential molecular mechanisms based on previous literatures. Please see pages 12–13 – Lines 535–557.

We apologize for this oversight in our original submission, and sincerely thank eLife Editors and Reviewers for this critique.

4. Since the antennal lobe is a 3D structre, we would like the authors represent their 2D models as 3D? (Does their model hold up?)

We agree that the antennal lobe is a 3D structure despite its relatively short anterior-posterior axis at early stages (~20 µm at 12h APF). To visualize PN dendrite targeting in 3D, we generate videos showing 3D rendering of z stacks of labeled PN dendrites in 12h APF antennal lobes with rotation along the y axis (Figure 3 – video 1, Figure 4 – video 1 and Figure 8 – video 1).

3D visualization reveals that PN dendrites were “located primarily on the periphery of the antennal lobe, whereas the center housed the axon bundle projecting out of the antennal lobe. Some dendrites could reach almost the entire depth, suggesting active exploration of the surroundings in many directions. While 3D projections provide rich details in depth and different viewing angles, we did not find apparent relationship between birth order and dendrite targeting along the anterior-posterior axis, at least for the examined PN types at 12h APF. Thus, the approximate 2D projection (Figure 3E2–4) conveys the logic of dendrite patterning effectively.” Please see page 6 – Lines 240–249.

We also suggest that the authors experimentally test their prediction. This could be by showing that a later-born neuron from adPN lineage will always target further clockwise. Or they could use Chinmo to change the temporal identity of the neurons. (Or any similar experiment they choose). If not, we suggest that they revisit their text to tone down their claim of dendrites targeting according to birth order.

Using MARCM and specific driver lines, we have access to four approximate temporal cohorts of adPNs based on their birth timing: (1) early, (2) mid-early, (3) mid-late and (4) late larval born adPNs. Analyses of their dendrite targeting have shown that a later-born adPN will always target further clockwise (see Figure 3D).

We are also keen on understanding the molecular mechanisms linking PN temporal identity to initial dendrite targeting. Indeed, Chinmo is known to specify the temporal identity of adPNs (Chinmo protein level is high in early-born and low in late-born PNs); loss of chinmo in the firstborn DL1 PNs leads to mistargeting to glomerulus targeted by the fourth-born D PNs (Zhu et al., 2006). This provides a molecular link between temporal identity and final glomerular targeting. However, as DL1 PNs and D PNs are both early-born PNs, we expect the changes in the initial dendrite targeting, if any, in DL1 PNs mutant for chinmo to be very subtle to observe. Currently, we are in the process of examining the transcriptome profiles among different cohorts to identify key molecules that create the rotation pattern. This will take many months of further work.

In the manuscript, we have avoided using strong statements like ‘birth order instructs dendrite targeting’.

Reviewer #1 (Recommendations for the authors):

I appreciate the quality and extent of the work presented in this manuscript and have only comments related to its presentation.

1. I find great value in describing how the earliest events in the birth of the neuron – through temporal patterning – translate to its target specification. This is an important area in neurodevelopment and one into which inroads have been made in the recent past. Much of this work has been in the ventral nerve cord and the optic lobe. It would benefit this manuscript immensely to place their work within this context.

We thank Reviewer #1 for pointing out the outstanding work investigating the temporal patterning in the ventral nerve cord and the optic lobe. We have added text and relevant references to the Discussion to place our study in this context. Please see our response to Essential Revision #3 for details.

2. The manner in which the study is currently presented gives the (false) impression that this is 'merely' a descriptive study that conveys in more detail an already known phenomenon. This is likely because the authors have restricted their reference to literature on the antennal lobe. The authors should present this work in the framework of formal possibilities of how birth order might affect targeting. Currently, the articulation of the problem they are addressing is too generic.

We took Reviewer #1’s advice and now discuss the possible molecular mechanisms underlying how PN birth order might affect dendrite targeting. Please see our response to Essential Revision #3 for details.

Reviewer #2 (Recommendations for the authors):

I have some specific comments for the authors:

1. Adult-specific antennal lobes were first built outside the larval antennal lobe and then took over the larval antennal lobe territory. They also observed that embryonic-born PNs retracted and extended dendrites simultaneously at spatially distinct regions. It was unexplained and undiscussed if the larval antennal lobes had a footprint left at that region to influence larval-born PN dendritic targeting, such as glial cells, unpruned dendrites, or presynaptic partners. And it remains to be addressed whether the rotation of initial dendritic targeting of PNs is related to the remnants of larval-specific antennal lobes.

We thank Reviewer #2 for pointing out the potential involvement of the larval-specific antennal lobe in the initial dendrite map formation of the adult-specific antennal lobe. We have added into Discussion the following quoted test from our lab found that “the larval-specific ORN axons secrete semaphorins, Sema-2a and Sema-2b, which act as repulsive ligands for dendrites of Sema-1a-expressing PNs (including DL1 PNs) (Komiyama et al., 2007; Sweeney et al., 2011).

As the larval-specific lobe is located ventromedial to the adult-specific lobe, Sema-2a/b and Sema-1a form opposing gradients along the dorsolateral-ventromedial axis. When DL1 PNs (the first-born/developed) begin to target their dendrites, this repulsive action could destabilize branches in the ventromedial direction and thus favor dorsolateral targeting. This provides a plausible explanation as to why the adPN rotation pattern begins at the dorsolateral position.” Please see page 13 – Lines 566–576.

2. Unlike the anterodorsal lineage that generates monoglomerulous PNs continuously, the lateral lineage intermingles the birth of monoglomerulous PNs (studied in this manuscript) and antennal mechanosensory and motor center (AMMC) PNs during neurogenesis (Lin et al., 2012, PLoS Biology). While it is convincing adPNs born around the same time form a cohort to target dendrites to similar territory, it is unclear if those AMMC PNs which are born between monoglomerulous PNs form a cohort with those PNs and target their dendrites to similar territory.

Reviewer #2 is correct that the lateral lineage produces 5 distinct PN classes in an intercalated manner: monoglomerulous PNs (mPNs), unilateral PNs, bilateral PNs, AMMC PNs and SOG PNs (Lin et al., 2012). As only mPNs are GH146+, we have not characterized the patterning of the other 4 PN types and therefore do not know if AMMC PNs born between mPNs share a similar targeting territory at any developmental stage.

Despite the lack of data, we find the point raised by Reviewer #2 very intriguing. Although AMMC PNs do not innervate the antennal lobe in the adult brain, whether they do so during development is not known. Cell-type specific labeling in the early developing brain, similar to what we have done for the mPNs, could provide invaluable insights into how neurons produced from the same lineage contribute to multiple circuitries that endow diverse sensory modalities. Nonetheless, as we focus on how wiring specificity arises in the olfactory map, analyses of other types of PNs are beyond the scope of the current work.

Please find relevant text changes in the Introduction: page 2 – Lines 79–82.

Besides, more lPNs (7) than adPNs (3) were categorized as 'early-born', and I was wondering if those 'early-born' lPNs can be further partitioned into smaller cohorts if AMMC PNs are considered.

Unfortunately, we currently do not have tools to label early-born lPNs at higher resolution, and therefore do not know whether the early-born lPNs can furthered be partitioned into smaller cohorts. Neither do we know whether AMMC PNs born in between would act as separators.

3. The authors proposed a compelling model about how PNs chose initial dendritic targeting territory based on its lineage and birth timing and showed a clock-like rotation as the targeting pattern. However, the antennal lobe is actually a 3D structure. 2D projection looks very intriguing, but it does not really reflect how targeting territory is selected in a 3D space. It might be more accurate to revise it as a 3D model.

We totally agree that a 3D model would provide a clearer picture of dendrite targeting during the initial map formation, and therefore provide videos showing the 3D visualization. Please see our detailed response in Essential Revision #4.

4. The definition of 'early', 'middle', and 'late' born PNs from both lineages is not very clear. Based on birth timing (what interval?) or dendrite targeting? Why anterodorsal lineage has fewer early-born PNs than the lateral lineage (3 vs. 7)?

We note that the heat shock time window to induce MARCM clones of the first-born DL1 PNs is wide (from 0 to 60h ALH), as reported previously (Jefferis et al., 2001). When we applied heat shock at 42–48h ALH to access early-born adPNs, most of the clones (>80%) were still DL1 PNs (Figure 3 —figure supplement 2E). This is likely because the neuroblast that gives rise to adPNs is arrested at G2 until quite sometime after larval hatching. This might cause the difference in the number of PN types in the early-born cohorts between adPN and lPN lineages.

5. In this manuscript, many neurons from the lateral lineage were left undiscussed. It might be good to remind readers that this manuscript is focusing on the monoglomerulous PNs only; interneurons and other types of PNs from the lateral lineage won't be discussed in the current work.

We thank Reviewer #2 for the advice and now remind readers that our work focuses on the wiring specificity of monoglomerular PNs only. This has been added to the Introduction. Please see page 2 – Lines 79–82.

Reviewer #3 (Recommendations for the authors):

I find the paper a strong candidate for eLife. The genetics is exceptional and the effort to comprehensively dissect the targeting of as many projection neurons as possible is both impressive and commendable. The ex-vivo time-lapse imaging is likewise super-impressive.

A few points that should be strengthened in my opinion:

1) Most of the figures represent convincing qualitative information without giving us any quantitative measures. At a very minimum, I would like to know how many neurons or brains (or both) were images and gave a consistent finding. Even better would be to find ways to describe the variability between brains. I understand that the lack of a "standard brain" for these developmental stages makes this more complicated but perhaps a course resolution would do.

We thank Reviewer #3 for pointing out the need of quantifications. We now provide the sample size for each genotype in the figure legends. We also add a new table (Supplementary file 1) describing different types of variations among individuals as well as measures we took to minimize them. Please see details in our response to Essential Revision #1.

2) I am not convinced by the statement that "groups" of neurons (grouped by birth date) target their dendrites to the same location. There are even a few projection neurons that belong to two groups – what does this mean? The clockwise rotation model should, in principle, offer a way to test this – no? It predicts that regardless of the stage, always the next-born neuron should target the clockwise correct location compared to the previous. This should strengthen the statement and verify if indeed there are groups – of indistinguishable (at this stage) dendrites…

We apologize for the use of “groups”, which might falsely imply that PNs themselves are intrinsically arranged into discrete groups based on their birth order. We have now used “approximate temporal cohorts” instead of “groups” and defined the cohorts “based on birth timing that corresponds to the heat shock time we applied to induce single-cell MARCM clones”. Please see detailed definition of each cohort in page 5 – Lines 209–215.

Indeed, “we note that DM6 and VA1v PNs were assigned to both cohorts of mid-late and lateborn adPNs, reflecting the nature of short birth timing differences and overlaps between adjacent cohorts” (page 2 – Lines 215–217). This also suggests that PNs are unlikely to be arranged into discrete groups.

For experiments to test the rotation model, please see our response in Essential Revision.

We have removed phrases such as “grouping by birth order” from the text and figures.

3) While I don't necessarily think that every paper needs to include mechanistic experiments, the two-step model presented in this manuscript, coupled with the many dendrite-targeting mutants that the Luo lab has previously generated, really makes it compelling to check if they are required for the initial targeting or later refinement. So for example, is the initial age and lineage dependent targeting normal in Sema1a; Ten-a/m; etc… Of course – does the final targeting depend on correct initial targeting. This is not absolutely necessary but adding some mechanistic aspects would make the study much more compelling to me.

We thank Reviewer #3 for raising these questions. Previous studies from our lab indeed demonstrate the loss of Sema-1a causes mistargeting of DL1 PN dendrites as early as 16h APF.

More importantly, such mistargeting phenotypes were observed consistently throughout development as well as in adulthood. These pieces of evidence illustrate that the initial dendrite targeting is important to the final targeting. We now add text describing the importance of the initial map in the Discussion. Please see page 14 – Lines 601–608.

4) If I understand correctly, previous data from the Luo lab has shown that the ORN-PN map is extremely stable, even if you kill or inactivate specific ORN/PNs. In light of this new study, PN-PN interactions have the potential to be important. Could adPNs affect the targeting of lPNs? Or vice versa? If this was not tested before, then perhaps even just discussing the option, rather than doing the experiments, seems like a logical step to me.

Reviewer #3 is right about the wiring stability of the adult olfactory map once PN-ORN connections are established (Berdnik et al., 2006). We note that because of the technical limitations (availability of drivers with early onset), the Berdnik et al. study was restricted to perturbing the olfactory circuit after wiring specificity has largely been established.

Given the robust PN dendritic dynamics seen in initial targeting process (Figures 5–8), we agree with the reviewer that whether adPNs and lPNs may reciprocally affect dendrite targeting is a very intriguing question. Although we currently do not have data to provide answers, we discuss the experimental designs that could address it in future works. See page 13 – Lines 558–565 in the Discussion.

https://doi.org/10.7554/eLife.85521.sa2

Article and author information

Author details

  1. Kenneth Kin Lam Wong

    Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, United States
    Contribution
    Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0002-5597-4051
  2. Tongchao Li

    Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, United States
    Present address
    Liangzhu Laboratory, MOE Frontier Science Center for Brain Science and Brain-machine Integration, State Key Laboratory of Brain-machine Intelligence, Zhejiang University, Hangzhou, China
    Contribution
    Resources, Investigation, Methodology, Writing – review and editing
    For correspondence
    ltongchao@outlook.com
    Competing interests
    No competing interests declared
  3. Tian-Ming Fu

    Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, United States
    Present address
    Department of Electrical and Computer Engineering, Princeton University, Princeton, United States
    Contribution
    Resources, Data curation, Investigation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-6265-0859
  4. Gaoxiang Liu

    Advanced Bioimaging Center, Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    Contribution
    Resources, Data curation, Investigation, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
  5. Cheng Lyu

    Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, United States
    Contribution
    Resources, Methodology, Writing – review and editing
    Competing interests
    No competing interests declared
  6. Sayeh Kohani

    Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, United States
    Contribution
    Data curation, Investigation
    Competing interests
    No competing interests declared
  7. Qijing Xie

    Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, United States
    Contribution
    Data curation, Investigation, Writing – review and editing
    Competing interests
    No competing interests declared
  8. David J Luginbuhl

    Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, United States
    Contribution
    Resources, Data curation, Writing – review and editing
    Competing interests
    No competing interests declared
  9. Srigokul Upadhyayula

    1. Advanced Bioimaging Center, Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    2. Molecular Biophysics and Integrated Bioimaging Division, Lawrence Berkeley National Laboratory, Berkeley, United States
    3. Chan Zuckerberg Biohub, San Francisco, United States
    Contribution
    Resources, Supervision, Writing – review and editing
    Competing interests
    No competing interests declared
  10. Eric Betzig

    1. Howard Hughes Medical Institute, Janelia Research Campus, Ashburn, United States
    2. Advanced Bioimaging Center, Department of Molecular and Cell Biology, University of California, Berkeley, Berkeley, United States
    3. Departments of Molecular and Cell Biology and Physics, Howard Hughes Medical Institute, Helen Wills Neuroscience Institute, University of California, Berkeley, United States
    Contribution
    Resources, Supervision, Writing – review and editing
    Competing interests
    No competing interests declared
  11. Liqun Luo

    Department of Biology, Howard Hughes Medical Institute, Stanford University, Stanford, United States
    Contribution
    Conceptualization, Supervision, Funding acquisition, Investigation, Methodology, Project administration, Writing – review and editing
    For correspondence
    lluo@stanford.edu
    Competing interests
    No competing interests declared
    ORCID icon "This ORCID iD identifies the author of this article:" 0000-0001-5467-9264

Funding

National Institutes of Health (R01 DC005982)

  • Liqun Luo

Philomathia Foundation

  • Gaoxiang Liu
  • Srigokul Upadhyayula

Chan Zuckerberg Initiative

  • Srigokul Upadhyayula

National Institutes of Health (1K99DC01883001)

  • Tongchao Li

Howard Hughes Medical Institute

  • Eric Betzig
  • Liqun Luo

The funders had no role in study design, data collection and interpretation, or the decision to submit the work for publication.

Acknowledgements

We thank the Luo lab members for constructive feedback on the manuscript; Tzumin Lee for sharing equipment at Janelia Research Campus; Luke Lavis for sharing JF dyes. This work was supported by a grant from NIH (R01 DC005982 to LL). TL was supported by NIH 1K99DC01883001. GL and SU are funded by Philomathia Foundation. SU is funded by the Chan Zuckerberg Initiative Imaging Scientist program. SU is a Chan Zuckerberg Biohub Investigator. EB and LL are HHMI investigators.

Senior Editor

  1. K VijayRaghavan, National Centre for Biological Sciences, Tata Institute of Fundamental Research, India

Reviewing Editor

  1. Sonia Sen, Tata Institute for Genetics and Society, India

Reviewer

  1. Sonia Sen, Tata Institute for Genetics and Society, India

Version history

  1. Received: December 11, 2022
  2. Preprint posted: December 29, 2022 (view preprint)
  3. Accepted: March 27, 2023
  4. Accepted Manuscript published: March 28, 2023 (version 1)
  5. Version of Record published: May 18, 2023 (version 2)

Copyright

© 2023, Wong et al.

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.

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  1. Kenneth Kin Lam Wong
  2. Tongchao Li
  3. Tian-Ming Fu
  4. Gaoxiang Liu
  5. Cheng Lyu
  6. Sayeh Kohani
  7. Qijing Xie
  8. David J Luginbuhl
  9. Srigokul Upadhyayula
  10. Eric Betzig
  11. Liqun Luo
(2023)
Origin of wiring specificity in an olfactory map revealed by neuron type–specific, time-lapse imaging of dendrite targeting
eLife 12:e85521.
https://doi.org/10.7554/eLife.85521

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