Systematic morphological and morphometric analysis of identified olfactory receptor neurons in Drosophila melanogaster

  1. Cesar Nava Gonzales
  2. Quintyn McKaughan
  3. Eric A Bushong
  4. Kalyani Cauwenberghs
  5. Renny Ng
  6. Matthew Madany
  7. Mark H Ellisman
  8. Chih-Ying Su

  • Curated by eLife

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    Evaluation Summary:

    Nava Gonzales et al. have reconstructed in unprecedented detail the morphology of olfactory sensory neurons (OSNs) and supporting cells within the sensilla in D. melanogaster, characterising the majority of sensory hairs, and OSN types. The morphometric dataset collected will be a reference point for the field of olfaction research in Drosophila, and furthermore might inspire similar analyses of other sensory systems, building our understanding of how peripheral morphological features contribute to sensory neuron processing.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

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Abstract

The biophysical properties of sensory neurons are influenced by their morphometric and morphological features, whose precise measurements require high-quality volume electron microscopy (EM). However, systematic surveys of nanoscale characteristics for identified neurons are scarce. Here, we characterize the morphology of Drosophila olfactory receptor neurons (ORNs) across the majority of genetically identified sensory hairs. By analyzing serial block-face electron microscopy images of cryofixed antennal tissues, we compile an extensive morphometric data set based on 122 reconstructed 3D models for 33 of the 40 identified antennal ORN types. Additionally, we observe multiple novel features—including extracellular vacuoles within sensillum lumen, intricate dendritic branching, mitochondria enrichment in select ORNs, novel sensillum types, and empty sensilla containing no neurons—which raise new questions pertinent to cell biology and sensory neurobiology. Our systematic survey is critical for future investigations into how the size and shape of sensory neurons influence their responses, sensitivity, and circuit function.

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  1. Version published to 10.7554/elife.69896 on eLife
  2. eLife

    Author Response:

    Reviewer #1:

    Nava Gonzales et al. have reconstructed in unprecedented detail the morphology of olfactory sensory neurons (OSNs) within their sensilla in D. melanogaster, characterising the majority of sensory hairs, and OSNs types. To that end they used 8 datasets - 7 of which had been previously published - of serial block-face electron microscopy (SBEM) images where different individual OSN classes were genetically labelled in each dataset. The morphometric dataset collected will be a reference point for the field of olfaction research in Drosophila, and furthermore might inspire similar analyses of other sensory systems, building our understanding of how peripheral morphological features contribute to sensory neuron processing. In addition, they made several observations that warrant follow up studies in the future. These include: 1) Finding what seems to be new sensillum types, and identification of variation in the number of neurons within a single sensillum class, including empty sensilla. 2) mitochondrial enrichment in the dendritic base of certain OSN classes, 3) the presence of extracellular vacuoles within the sensillum lymph, likely derived from the tormogen accessory cell. The paper is purely descriptive but is a valuable addition to the literature and the claims made in the paper are well justified by the results. I have a few comments that I detail in the below.

    We thank the reviewer for sharing with us their appreciation for our study.

    • The authors should include more detail as to how the different sensillum classes were identified. The only information given is: "Within a morphological class, sensillum identity was determined by the number of enclosed neurons, the relative position of the sensillum on the antenna, as well as by genetic labelling when this information was available", and "we distinguished ab2 from ab3 by its characteristic antennal location". However, it is worth noting that while sensilla distribution across the antennae is heterogeneous and indeed specific sensillum types are restricted to particular domains, the distribution of many sensillum types follows a "salt and pepper" pattern, intermingling with each other. This is specifically the case for ab2 and ab3 sensilla, both found in partially overlapping regions of the antennae. Therefore, a more detailed description in the methods as to how each sensillum type was assigned will aid the reader understand how the authors reached their conclusions. Furthermore, the authors should avoid circular arguments, such as the one presented for ab2 sensilla, where the identification was made based on position (with the caveat highlighted above) and on the difference in size, but this difference is then used as part of the results, making the argument circular.

    We thank the reviewer for raising this point, in particular regarding the distinction between ab2 and ab3 sensilla. In the Results, we have now clarified that “Among the two large basiconic sensilla that house two neurons, we distinguished ab2 from ab3 by its lack of DAB staining in the Or22a dataset, in which ab3A was genetically labeled by APEX2. Apart from the Or22a dataset, an ab2 sensillum was identified in the Or7a dataset on the basis of its proximity to the labeled ab4 sensilla, because ab3 is not found in the same topographical region as ab4 (de Bruyne et al., 2001).”

    We have also described how each sensillum type was identified in the revised Source Data for Table 1.

    • Following on this point, one of the novel basiconic sensilla identified abx(3) is undistinguishable in terms of morphological features from ab3 sensilla. How was it then distinguished from ab3? Was it due to the lack of genetic marking? This is not explicitly stated in the manuscript and needs to be specified. Furthermore, the authors propose that this sensillum type could be an ab1 sensilla that is missing the ab1D neuron. How did they arrive to this conclusion? If it was based on location, this needs to be explained more explicitly.

    We apologize for the confusion. As indicated in the subheading, abx(3) designates a novel large basiconic sensillum type that houses three ORNs. In contrast, ab3 is a well-characterized large basiconic sensillum that are known to house only two ORNs. Therefore, we can distinguish abx(3) from ab3 according to the number of neurons found in each sensillum. To further clarify this matter, we have also indicated how each sensillum type was identified in the revised Source Data for Table 1.

    In addition, we wish to clarify that we proposed, instead of concluded, that abx(3) may represent an ab1 subset based on the similarity of their A and B neuron size differential (not based on antennal location). However, we agree with the reviewer: we cannot rule out the possibility that abx(3) is instead an ab3 subset, or houses three uncharacterized orphan ORNs. Therefore, we considered these possibilities in the revised Results, which reads “However, it is also possible that abx(3) represents an ab3 subset, or houses three uncharacterized orphan ORNs whose receptors have not yet been reported.”

    A suggestion is to show in Figure 1 a diagram of an antennae and indicate from where in the antennae each of the datasets was taken. Furthermore, in subsequent figures it would be good to show on a schematic antennae the approximate location of the described sensilla, and specify from which dataset they were reconstructed.

    We thank the reviewer for the excellent suggestion. We have included a schematic antenna in the revised Figure 1 to indicate the antennal regions covered by individual SBEM volumes.

    For each sensillum, we have also specified the source dataset from which it was identified (Source Data for Table 1). Further detailed information can be found in a new “Source Data for Figure 1” file.

    • I have some concerns regarding some of the claims made for ab2 sensilla, as these are based on a single sensillum reconstruction (Table 2, n=1 for ab2 sensilla).

    We appreciate the reviewer’s concern. Although we identified a total of four ab2 sensilla, only one of them contained neurons that could be segmented in their entirely. However, we note that in comparison to the ab3 neurons, the ab2 neurons are highly distinctive based on its striking A/B size differential (2.7 : 1 for ab2, Figure 6G, and 1.5 : 1 for ab3, Figure 7C).

    • The discovery of a large number of mitochondria in the inner dendritic segment of some OSN classes but not others is intriguing. Although there seem to be no correlation between this and the size of the soma and therefore spike amplitude generated by each OSN (see ab5A vs ab5B sensilla). It would be interesting if the authors could generate some graphs correlating the number of mitochondria with some physiological parameters previously published, such as spike amplitude, and resting spike frequency of each OSN type.

    We thank the reviewer for the suggestion. In preliminary analysis, we did not observe any correlation between mitochondria number and other ORN features. Although we prefer not to show this negative result in a separate figure, we have incorporated the reviewer’s suggestion by expanding Table 2 to include the mitochondria number.

    In addition, we wish to clarify that the resting spike frequency is determined by the receptor expressed in the ORNs (Hallem et al., Cell, 2004), which is independent of whether the neuron is a large- or small-spike ORN. By extension, the resting spike frequency is independent of the neuron’s morphometric features.

    • Their findings on at4 sensilla imply that this sensillum type should be reclassified as at4_T2 and at4_T3, because at4_T2 contains only two neurons expressing Or82a and Or47b, while at4_T3 sensilla contains three neurons, expressing Or82a, Or47a and Or65a. This is extremely interesting and predicts that there would be more Or82a and Or47a neurons in the antennae than Or65a neurons, something unexpected given the previous assumption of a single at4 sensillum type with 3 neurons. Based on this finding the authors claim: "We show that not all ORNs expressing the same receptor are house in a singular sensillum type". This statement should be rephrased as it was known before that the same receptor can be housed in two sensillum types, as it is the case for Or35a being hosted in both ac3i and ac3ii sensilla, being paired with either Ir75b or Ir75c.

    We agree with the reviewer that the sentence may have overstated the novelty of our finding. We have therefore removed the statement in the revised text.

    Besides these comments, the manuscript provides plenty of novel and intriguing findings that will set the bases for many future investigations.

    Once again, we thank the reviewer for expressing their appreciation for the significance of our study.

    Reviewer #2:

    Gonzales et al., took advantage of high-end automated, volume-based EM technology, and genetic labelling thus providing an extensive 3D morphometric dataset of 122 olfactory receptor neurons (ORN, that is about 10 per cent of the reported number of ORNs on the antenna of Drosophila melanogaster) grouped in 33 ORN types and housed in 13 of the 19 known antennal sensilla types. For the ORNs morphometric measures, such as ORN soma size and dendritic branching pattern are analyzed. In addition, over 500 sensilla, derived from eight data sets, are identified, including new morphological types. Cellular features, such as empty sensilla, mitochondria number, extracellular vacuoles and extensive dendritic branching in distinct ORNs are described. In selected cases the structure and relationship to the supporting cell in sensilla (thecogen, tormogen and trichogen) are depicted. The studies goes beyond previous structural work done in this field by covering a large number of sensilla and its olfactory receptors.

    The sheer number and completeness of the data strongly complements our knowledge of the sensilla assembly and ORN types in Drosophila. Of particular interest is the ORN cell variability but also their generic structural features (such as soma size for the A and B neuron) reported in a large number of identified ORNs. All olfactory sensilla types (basiconica, trichodea, coelonica) are covered in this study. Therefore, the data presented here are valuable for the experimental neurobiologist for comparing functional properties in ORNs (from own single cell ORN recordings), and is also of potential use for comparative studies in other insects outside the Drosophila neuroscience community.

    In general, the manuscript is well organized. The figures, including figure legends, are nicely designed to give a comprehensive overview that is mostly well to read with the accompanying text. See, my suggesting for improvements below.

    The morphometric analysis is restricted to ORN macroscopic features, such as cell size and dendrite branching pattern of ORNs, cellular features, such as mitochondria distribution, or the relationship to the sensilla supporting cells are only analyzed in exemplified cases.

    I do recommend for a publication in e-life providing the authors make an effort for a more detailed discussion of their findings, and a more comprehensive introduction, e.g. for essential sensilla components such as support cells.

    We thank the reviewer for the careful reading of our manuscript and for expressing their appreciation for the significance of our study.

    For a wider audience of the neuroscience community the manuscript would much benefit from:

    1. by expanding your discussion with respect functional significance of your findings: How does your classification of ORN types compares to previous anatomical and functional studies ?

    We wish to clarify that our study focuses on the nanoscale morphological and morphometric features of sensilla and ORNs, instead of the distribution of sensilla on the antenna. Each SBEM volume samples a specific portion of the antenna covering the APEX2-labeled sensilla, making it difficult to precisely determine its relative antennal location. Therefore, we do not feel comfortable drawing direct comparison to other studies regarding the distribution of sensilla on the antenna, as that is not the focus of our study.

    To address the reviewer’s concern, we wrote in the beginning of Results section “In agreement with the characteristic topographical distribution of sensilla on the antenna (de Bruyne, Foster, & Carlson, 2001; Grabe et al., 2016; Shanbhag et al., 1999), the four morphological sensillum classes were unevenly represented in our eight SBEM datasets (Figure 1B,C).”

    How does our classification of ORN types compare to previous functional studies? We wish to clarify that the odor response profile of an ORN is predominantly determined by the receptor expressed in the neuron (Hallem et al., Cell, 2004), which is independent of whether the neuron is a large- or small-spike ORN. By extension, the odor response profile is independent of the neuron’s morphometric features. It is therefore of limited usefulness to search for any correlation between ORNs’ morphological features and odor response properties.

    However, we have incorporated the reviewer’s suggestion by revising the text to include key ligands for ORNs that respond to ethologically salient odors. In addition, we have included the following sentence in the revised Table 2 legend “The odor response profiles for many of the characterized ORNs can be found in the DoOR database (<http://neuro.uni- konstanz.de/DoOR/default.html>)” such that readers who are curious about the functional data can easily find the information.

    Is an 'empty sensillum' a novel finding ?

    Yes, it has never been described before, making the identification of empty sensilla an exciting and novel finding. To clarify the confusion, we have explicitly stated "such empty sensilla have never been reported before" in the revised text.

    How are physiological responses on the receptor level correlate with neurons' soma size and number of mitochondria ?

    We thank the reviewer for raising this interesting question. Currently, there is no clear relationship demonstrated between ORN soma size and physiological response properties.

    The only known functional significance of ORN size differential is its impact on the asymmetrical ephaptic interaction between compartmentalized ORNs, which we have investigated in detail in our previous publication (Zhang et al., 2019). We have summarized our prior findings in the main text, which reads “Indeed, ORNs housed in the same sensillum can inhibit each other by means of direct electrical interaction, termed ephaptic coupling, which can also modulate fruitfly behavior in response to odor mixtures (Su, Menuz, Reisert, & Carlson, 2012; Zhang et al., 2019). Strikingly, in most sensillum types, lateral inhibition is asymmetric between compartmentalized ORNs: the large-spike neuron is not only capable of exerting greater ephaptic influence but is also less susceptible to ephaptic inhibition by its small-spike neighbors. Mechanistically, this functional disparity arises from the size difference between grouped neurons. The large-spike ORN has a larger soma than its small-spike neighbor(s); this feature is translated into a smaller input resistance for the “A” neuron, thus accounting for its dominance in ephaptic interaction (Zhang et al., 2019).”

    On a similar note, there is also no clear relationship between ORN mitochondria number and odor response properties. However, to addressed the reviewer’s comment, we have now provided background information on mitochondria function in olfactory signaling “We note that in vertebrate ORNs, mitochondria play a direct role in regulating cytosolic Ca2+ response profile and thereby ensure a broad dynamic range for the neurons’ spike responses (Fluegge et al., 2012). Although it is unclear whether mitochondria play a similar role in insect olfactory signaling, a recent study shows that odor-induced Ca2+ signals in Drosophila ORNs are shaped by mitochondria (Lucke, Kaltofen, Hansson, & Wicher, 2020). Therefore, it will be interesting to investigate the functional significance of this striking mitochondrial disparity between grouped ORNs in future research.”

    Some ORNs express more than one receptor, as shown recently previous work by the Potter lab: Task (2020) Widespread Polymodal Chemosensory Receptor Expression in Drosophila Olfactory Neurons 2020.11.07.355651 .

    Although the multiplicity of receptors expressed in individual insect ORNs raises intriguing questions, this information is not directly related to our study. It has been shown that deleting or the tuning OR in an ORN does not change its spike amplitude (Dobritsa et al, Neuron, 2003; Hallem et al., Cell, 2004), which by extension suggests that the receptor does not influence the morphometric feature of an ORN. To explicitly demonstrate this point, we have now provided the information in the revised Introduction “Interestingly, deleting or substituting the tuning receptor for an ORN does not alter its characteristic spike amplitude (Dobritsa, van der Goes van Naters, Warr, Steinbrecht, & Carlson, 2003; Hallem et al., 2004), suggesting that this feature is independent of the receptor identity.”

    1. The Table 2, that gives a summary of your result, should be more informative and presented in broader context of what is known on the receptors you describe. . Please, give a reference to the DoOR database (http://neuro.uni-konstanz.de/DoOR/default.html) that provides an excellent overview of functional and anatomical properties of ORNs. Additional columns, e.g. ORN corresponding glomeruli for the their representation in the antennal lobe, -DoOR response, -OR co-receptors, or -best ligand by of would be very valuable.

    As suggested, we have included ORN glomerulus projection as an additional identifier in Table 2. The revised legend now includes: “ORN identity is indicated by the sensillum type, relative spike amplitude (A, B, C or D), odor-tuning receptor, and glomerular projection.”

    For clarity, and in consideration of the large information load, we focus on our own morphometric data in Table 2. For the same reasons, we also focus on the tuning receptors as a key ORN identifier without mentioning other co-expressed receptors of unknown function.

    Furthermore, we wish to clarify that the odor response profile of an ORN is predominantly determined by the tuning receptor expressed in the neuron (Hallem et al., Cell, 2004), which is independent of whether the neuron is a large- or small-spike ORN. By extension, the odor response profile is independent of the neuron’s morphometric features. It is therefore of limited usefulness to search for any correlation between ORNs’ morphological features and odor response properties.

    However, we have incorporated the reviewer’s suggestion by revising the text to include key ligands for ORNs that respond to ethologically salient odors. We have also included the following sentence in the revised Table 2 legend “The odor response profiles for many of the characterized ORNs can be found in the DoOR database (<http://neuro.uni- konstanz.de/DoOR/default.html>)” such that readers who are curious about the functional data can easily find the information.

    For Figure 1, a clearer description of the location and representation of the genetically /non-genetically ORN and sensilla types is necessary. A nice overview is given by Grabe (2016), see Figure 1, here.

    We thank the reviewer for the excellent suggestion. We have now added a new panel (Fig 1C) to illustrate the antennal regions covered by individual SBEM volumes.

    1. Do you plan to make your datasets publicly available in an open source platform ? In particular, the non-genetically labelled, but identified ORN types are candidates for other researchers to explore cellular features in more detail. Can you make statements of the preservation of the ultrastucture in these preparations ?

    Such efforts were made for the Drosophila brain connectome with data repositories provided by HHMI Janelia Research Campus and further suggestions for appropriate software (https://www.janelia.org/project-team/flyem).

    We thank the reviewer for raising this critical point. All eight SBEM image volumes described in this study have been deposited in the Cell Image Library (http://www.cellimagelibrary.org/home). We have also provided the accession numbers in the revised “SBEM datasets” under the Materials and Methods section.

    As mentioned in the Introduction and Material and Methods sections, the antennal tissues were high-pressure frozen and freeze-substituted (i.e. cryofixed), which optimally preserved the ultrastructure of cells. We note that the tissue preservation method has been described and discussed in detail in our prior publication (Tsang et al, eLife, 2018).

    To address the reviewer’s comment, we have now stated explicitly in the Introduction “Taking advantage of the CryoChem method, which we have previously developed to permit high-quality ultrastructural preservation of cryofixed and genetically labeled samples for volume EM (Tsang et al., 2018), we have acquired serial block-face scanning electron microscopy (SBEM) images of antennal tissues in which select ORNs expressed an membrane-tethered EM marker (APEX2-mCD8GFP or APEX2-ORCO) (Tsang et al., 2018; Zhang et al., 2019).”

  3. eLife

    Evaluation Summary:

    Nava Gonzales et al. have reconstructed in unprecedented detail the morphology of olfactory sensory neurons (OSNs) and supporting cells within the sensilla in D. melanogaster, characterising the majority of sensory hairs, and OSN types. The morphometric dataset collected will be a reference point for the field of olfaction research in Drosophila, and furthermore might inspire similar analyses of other sensory systems, building our understanding of how peripheral morphological features contribute to sensory neuron processing.

    (This preprint has been reviewed by eLife. We include the public reviews from the reviewers here; the authors also receive private feedback with suggested changes to the manuscript. Reviewer #2 agreed to share their name with the authors.)

  4. eLife

    Reviewer #1 (Public Review):

    Nava Gonzales et al. have reconstructed in unprecedented detail the morphology of olfactory sensory neurons (OSNs) within their sensilla in D. melanogaster, characterising the majority of sensory hairs, and OSNs types. To that end they used 8 datasets - 7 of which had been previously published - of serial block-face electron microscopy (SBEM) images where different individual OSN classes were genetically labelled in each dataset. The morphometric dataset collected will be a reference point for the field of olfaction research in Drosophila, and furthermore might inspire similar analyses of other sensory systems, building our understanding of how peripheral morphological features contribute to sensory neuron processing. In addition, they made several observations that warrant follow up studies in the future. These include: 1) Finding what seems to be new sensillum types, and identification of variation in the number of neurons within a single sensillum class, including empty sensilla. 2) mitochondrial enrichment in the dendritic base of certain OSN classes, 3) the presence of extracellular vacuoles within the sensillum lymph, likely derived from the tormogen accessory cell. The paper is purely descriptive but is a valuable addition to the literature and the claims made in the paper are well justified by the results. I have a few comments that I detail in the below.

    - The authors should include more detail as to how the different sensillum classes were identified. The only information given is: "Within a morphological class, sensillum identity was determined by the number of enclosed neurons, the relative position of the sensillum on the antenna, as well as by genetic labelling when this information was available", and "we distinguished ab2 from ab3 by its characteristic antennal location". However, it is worth noting that while sensilla distribution across the antennae is heterogeneous and indeed specific sensillum types are restricted to particular domains, the distribution of many sensillum types follows a "salt and pepper" pattern, intermingling with each other. This is specifically the case for ab2 and ab3 sensilla, both found in partially overlapping regions of the antennae. Therefore, a more detailed description in the methods as to how each sensillum type was assigned will aid the reader understand how the authors reached their conclusions. Furthermore, the authors should avoid circular arguments, such as the one presented for ab2 sensilla, where the identification was made based on position (with the caveat highlighted above) and on the difference in size, but this difference is then used as part of the results, making the argument circular.

    - Following on this point, one of the novel basiconic sensilla identified abx(3) is undistinguishable in terms of morphological features from ab3 sensilla. How was it then distinguished from ab3? Was it due to the lack of genetic marking? This is not explicitly stated in the manuscript and needs to be specified. Furthermore, the authors propose that this sensillum type could be an ab1 sensilla that is missing the ab1D neuron. How did they arrive to this conclusion? If it was based on location, this needs to be explained more explicitly. A suggestion is to show in Figure 1 a diagram of an antennae and indicate from where in the antennae each of the datasets was taken. Furthermore, in subsequent figures it would be good to show on a schematic antennae the approximate location of the described sensilla, and specify from which dataset they were reconstructed.

    - I have some concerns regarding some of the claims made for ab2 sensilla, as these are based on a single sensillum reconstruction (Table 2, n=1 for ab2 sensilla).

    - The discovery of a large number of mitochondria in the inner dendritic segment of some OSN classes but not others is intriguing. Although there seem to be no correlation between this and the size of the soma and therefore spike amplitude generated by each OSN (see ab5A vs ab5B sensilla). It would be interesting if the authors could generate some graphs correlating the number of mitochondria with some physiological parameters previously published, such as spike amplitude, and resting spike frequency of each OSN type.

    - Their findings on at4 sensilla imply that this sensillum type should be reclassified as at4_T2 and at4_T3, because at4_T2 contains only two neurons expressing Or82a and Or47b, while at4_T3 sensilla contains three neurons, expressing Or82a, Or47a and Or65a. This is extremely interesting and predicts that there would be more Or82a and Or47a neurons in the antennae than Or65a neurons, something unexpected given the previous assumption of a single at4 sensillum type with 3 neurons. Based on this finding the authors claim: "We show that not all ORNs expressing the same receptor are house in a singular sensillum type". This statement should be rephrased as it was known before that the same receptor can be housed in two sensillum types, as it is the case for Or35a being hosted in both ac3i and ac3ii sensilla, being paired with either Ir75b or Ir75c.

    Besides these comments, the manuscript provides plenty of novel and intriguing findings that will set the bases for many future investigations.

  5. eLife

    Reviewer #2 (Public Review):

    Gonzales et al., took advantage of high-end automated, volume-based EM technology, and genetic labelling thus providing an extensive 3D morphometric dataset of 122 olfactory receptor neurons (ORN, that is about 10 per cent of the reported number of ORNs on the antenna of Drosophila melanogaster) grouped in 33 ORN types and housed in 13 of the 19 known antennal sensilla types. For the ORNs morphometric measures, such as ORN soma size and dendritic branching pattern are analyzed. In addition, over 500 sensilla, derived from eight data sets, are identified, including new morphological types. Cellular features, such as empty sensilla, mitochondria number, extracellular vacuoles and extensive dendritic branching in distinct ORNs are described. In selected cases the structure and relationship to the supporting cell in sensilla (thecogen, tormogen and trichogen) are depicted. The studies goes beyond previous structural work done in this field by covering a large number of sensilla and its olfactory receptors.

    The sheer number and completeness of the data strongly complements our knowledge of the sensilla assembly and ORN types in Drosophila. Of particular interest is the ORN cell variability but also their generic structural features (such as soma size for the A and B neuron) reported in a large number of identified ORNs. All olfactory sensilla types (basiconica, trichodea, coelonica) are covered in this study. Therefore, the data presented here are valuable for the experimental neurobiologist for comparing functional properties in ORNs (from own single cell ORN recordings), and is also of potential use for comparative studies in other insects outside the Drosophila neuroscience community.

    In general, the manuscript is well organized. The figures, including figure legends, are nicely designed to give a comprehensive overview that is mostly well to read with the accompanying text. See, my suggesting for improvements below.

    The morphometric analysis is restricted to ORN macroscopic features, such as cell size and dendrite branching pattern of ORNs, cellular features, such as mitochondria distribution, or the relationship to the sensilla supporting cells are only analyzed in exemplified cases.

    I do recommend for a publication in e-life providing the authors make an effort for a more detailed discussion of their findings, and a more comprehensive introduction, e.g. for essential sensilla components such as support cells.

    For a wider audience of the neuroscience community the manuscript would much benefit from:

    1. by expanding your discussion with respect functional significance of your findings: How does your classification of ORN types compares to previous anatomical and functional studies ? Is an 'empty sensillum' a novel finding ? How are physiological responses on the receptor level correlate with neurons' soma size and number of mitochondria ? Some ORNs express more than one receptor, as shown recently previous work by the Potter lab: Task (2020) Widespread Polymodal Chemosensory Receptor Expression in Drosophila Olfactory Neurons 2020.11.07.355651 .

    2. The Table 2, that gives a summary of your result, should be more informative and presented in broader context of what is known on the receptors you describe. . Please, give a reference to the DoOR database (http://neuro.uni-konstanz.de/DoOR/default.html) that provides an excellent overview of functional and anatomical properties of ORNs. Additional columns, e.g. ORN corresponding glomeruli for the their representation in the antennal lobe, -DoOR response, -OR co-receptors, or -best ligand by of would be very valuable. For Figure 1, a clearer description of the location and representation of the genetically /non-genetically ORN and sensilla types is necessary. A nice overview is given by Grabe (2016), see Figure 1, here.

    3. Do you plan to make your datasets publicly available in an open source platform ? In particular, the non-genetically labelled, but identified ORN types are candidates for other researchers to explore cellular features in more detail. Can you make statements of the preservation of the ultrastucture in these preparations ?
      Such efforts were made for the Drosophila brain connectome with data repositories provided by HHMI Janelia Research Campus and further suggestions for appropriate software (https://www.janelia.org/project-team/flyem).

  6. Version published to 10.1101/2021.04.28.441861v1 on bioRxiv