HI-FISH: Whole brain in situ mapping of neuronal activation in Drosophila during social behaviors and optogenetic stimulation

  1. Kiichi Watanabe
  2. Hui Chiu
  3. David J Anderson

  • Curated by eLife

    eLife logo

    eLife Assessment

    This work reports an important new method for activity-dependent neuronal labeling in Drosophila using in situ hybridization, with the potential to establish a new standard in the field. The authors demonstrate the method's applicability by generating compelling evidence of the function of male-specific neurons in both aggression and courtship behaviors. These results and the new method will be of great interest to the neuroscience community.

Reviewed by

Read the full article

Listed in

Log in to save this article

Abstract

Monitoring neuronal activity at single-cell resolution in freely moving Drosophila engaged in social behaviors is challenging because of their small size and lack of transparency. Extant methods, such as Flyception, are highly invasive. Whole-brain calcium imaging in head-fixed, walking flies is feasible but the animals cannot perform the consummatory phases of social behaviors like aggression or mating under these conditions. This has left open the fundamental question of whether neurons identified as functionally important for such behaviors using loss- or gain-of-function screens are actually active during the natural performance of such behaviors, and if so during which phase(s). Here we perform brain-wide mapping of active cells expressing the Immediate Early Gene hr38 using a high-sensitivity/low background FISH amplification method called HCR-3.0. Using double-labeling for hr38 mRNA and for GFP, we describe the activity of several classes of aggression-promoting neurons during courtship and aggression, including P1 a cells, an intensively studied population of male-specific interneurons. Using HI-FISH in combination with optogenetic activation of aggression-promoting neurons (opto-HI-FISH) we identify candidate downstream functional targets of these cells in a brain-wide, unbiased manner. Finally we compare the activity of P1 a neurons during sequential performance of courtship and aggression, using intronic vs. exonic hr38 probes to differentiate newly synthesized nuclear transcripts from cytoplasmic transcripts synthesized at an earlier time. These data provide evidence suggesting that different subsets of P1 a neurons may be active during courtship vs. aggression. HI-FISH and associated methods may help to fill an important lacuna in the armamentarium of tools for neural circuit analysis in Drosophila .

Article activity feed

  1. Version published to 10.7554/elife.92380.2 on eLife
  2. Version published to 10.7554/elife.92380 on eLife
  3. eLife

    eLife Assessment

    This work reports an important new method for activity-dependent neuronal labeling in Drosophila using in situ hybridization, with the potential to establish a new standard in the field. The authors demonstrate the method's applicability by generating compelling evidence of the function of male-specific neurons in both aggression and courtship behaviors. These results and the new method will be of great interest to the neuroscience community.

  4. eLife

    Reviewer #1 (Public review):

    Summary:

    The authors have nicely demonstrated the efficiency of the HCR v.3.0 using hr38 mRNA expression as a marker of neuronal activity. This is very important in the Drosophila neuroscience field as in situ hybridization in adult Drosophila brains have been so far very challenging to do and replicate. The HCR v.3.0 has been described before [Choi et al., (2018)] and is now the property of the non-profit organization Molecular Technologies, who are the ones responsible for designing the probes. Here, taking advantage of this new FISH method, the authors have demonstrated the use of the FISH to identify neurons activated by a specific behavioral task using hr38 mRNA as a marker of neuronal activation. They named their method HI-FISH.
    In addition, based on the catFISH method [Guzowski et al., 1999], the authors were able to distinguish between newly activated neurons (nascent nuclear mRNA) and mature hr38 mRNA showing an earlier activation. They describe this method as HI-catFISH.
    Finally, to test what are the neurons activated downstream of their neuronal group of interest, the authors combined the HI-FISH method with optogenetic using chrimson. They named this method opto-HI-FISH.

    Using these three new methods, the authors have addressed the following biological question: are love and aggressiveness neuronally the same in Drosophila?
    Here, the authors focused on the male specific P1a neurons which are activated by both an aggressive context (male-male encounter) and sexual context (male female encounter).

    Strengths:

    The demonstration of the efficiency of the method is very convincing and well-performed. It gives the will for the reader to apply the method to their own subject.

    Weaknesses:

    The more neurons are present, the more difficult it is to identify neurons. This is something to take into account when applying these methods.

  5. eLife

    Reviewer #2 (Public review):

    Summary:

    Watanabe et al. introduce a novel approach for activity-dependent labeling of neural circuits in Drosophila at single-cell resolution, based on detecting the expression of the immediate early gene Hr38 using in situ hybridization. While activity mapping of neurons during specific behaviors is well-established in rodent models, its application in Drosophila has been limited, primarily due to technical constraints. By overcoming these challenges, this study tackles an important and timely issue, providing a foundational tool that will serve as a key reference in the field of circuit neuroscience.

    Strengths:

    The principal strength of this method lies in its versatility and high sensitivity. It can be applied to a broad range of biological questions and enables the investigation of dynamic transcriptional regulation across an unlimited number of genes with a strong signal-to-noise ratio. As such, it holds great potential for widespread use across research labs.

    Weaknesses:

    No major weaknesses; all concerns have been adequately addressed.

  6. eLife

    Author response:

    Reviewer #1:

    Response to Public Review

    We thank the reviewer for taking the time to carefully read our paper and to provide helpful comments and suggestions, most of which we have incorporated in our revised manuscript. One of this reviewer’s (and reviewer #2’s) main concerns was that the confocal images provided in some cases did not appear to reflect the quantitative data in the bar graphs. These images were provided only for illustrative purposes, to give the reader a sense of what the primary data look like. The reviewer may not have appreciated that the quantitative data reflect counts of RNA smFISH signals (dots) in hundreds of cells collected through z-stacks comprising multiple optical sections in multiple flies for each condition For example, in P1a control condition (in Figure 2A), we have analyzed 135 neurons from 8 individuals. There, the number of z-planes ranged from 3 to 8 per hemisphere. It is generally not possible to find a single confocal section that encompasses quantitatively the statistics that are presented in the graphs. Presenting the data as an MIP (Maximum Intensity Projection, i.e., collapsed z-stack) in a single panel would generate an image that is too cluttered to see any detail. We have now included, for the reader’s benefit, additional example confocal sections in both a z-stack and from the opposite hemisphere, in Supplemental Figure S4D. We have also inserted clarifying statements in the text on p. 7 (lines 154-156).

    Another suggestion from Reviewer #1 is that "it would be more informative to separate in the quantification between the GAL4-expressing neurons and the non-expressing ones" based on the presented pictures where more non-P1a neurons (that the reviewer speculates may be pC1-type neurons) are activated by a male-male encounter than by a male-female encounter, while the P1a-positive neurons seem to be more responsive during courtship behavior. In this paper, we were not looking at pC1 neurons and did not try to answer which neuronal population(s) outside of the P1a population is/are responsible for aggression and/or courtship. Rather, we focused on P1a neurons and addressed whether P1a neurons that induce both aggression and courtship behavior when they are artificially activated (Hoopfer et al. 2015) are also naturally activated during spontaneous performance of these two social behaviors. However, this result did not exclude the possibility that P1a neurons were inactive during naturalistic courtship or aggression. Our data in the current manuscript provide further experimental evidence in support of the idea that P1a neurons as a population play a role in both of these behaviors. Moreover, we provided data identifying P1a neurons activated only during aggression or during courtship (or both). However this does not exclude that pC1 or other neighboring populations are activated during aggression as well (See also the response to 'Recommendations For The Authors' and text lines 151-154).

    In Figure 3, we used opto-HI-FISH to identify candidate downstream targets (direct or indirect) of P1a neurons. We used 50 Hz Chrimson stimulation to activate P1a neurons to induce expression of Hr38 and identified Kenyon cells in the mushroom body (MB) and PAM neurons (as well as pCd neurons) as potential downstream targets of P1a cells. In Figure 3 – supplement we performed calcium imaging of KCs and PAM neurons in response to P1a optogenetic stimulation to confirm independently our results from the Hr38 labeling experiments. That control was the purpose of that supplemental experiment.

    Based on those imaging data, the reviewer asked the further question of which [natural] behavioral context induces Hr38 expression in these populations (i.e., mating or aggression). This question is reasonable because our calcium imaging data (Figure 3-supplement) showed that both Kenyon cells and PAM neurons are active only during photo-stimulation of P1a neurons. Our previous behavioral studies (Inagaki et al., 2014; Hoopfer et al., 2015) showed that 50 Hz photo-stimulation of P1a neurons in freely moving flies induced unilateral wing extension during stimulation, while aggression was observed only after the offset of the stimulation (Hoopfer et.al., 2015). Based on the comparison of those behavioral data to the imaging results in this paper, the reviewer suggested that Kenyon cells and PAM neurons are activated during courtship rather than during aggression. This is certainly a possible interpretation. However it is difficult to extrapolate from behavioral experiments in freely moving animals to calcium imaging results in head-fixed flies, particularly with response to neural dynamics. Furthermore, Hr38 expression, like that of other IEGs (e.g., c-fos), may reflect persistently activated 2nd messenger pathways (e.g., cAMP, IP3) in Kenyon cells and PAM neurons that are not detected by calcium imaging, but that nevertheless play a role in mediating its behavioral effects. We still do not understand the mechanisms of how optogenetic stimulation of P1a neurons in freely behaving flies induces aggression vs. courtship behavior. Although 50 Hz stimulation of P1a neurons does not induce aggressive behavior during photo-stimulation, it is possible that this manipulation activates both aggression and courtship circuits, but that the courtship circuit might inhibit aggressive behavior at a site downstream of the MB (e.g., in the VNC). Once stimulation is terminated and courtship stops the fly would show aggressive behavior, due to release of that downstream inhibition (see Models in Anderson (2016) Fig 2d, e). In that case, there would be no apparent inconsistency between the imaging data and behavioral data. We agree that the reviewer's question is interesting and important but we feel that answering this question with decisive experiments is beyond the scope of this manuscript.

    Finally, Reviewer #1 suggested a method to evaluate the Hr38 signals in the catFISH experiment of Figure 4. We appreciate their suggestions, but the way that we evaluated the Hr38 signals was basically the same as the way the reviewer suggested. We apologize for the confusion caused by the lack of detailed descriptions in the original manuscript. We have now revised the methods section to explain more clearly how we define the cells as positive based on Hr38EXN and Hr38INT signals.

    Response to Recommendations for the authors:

    “To strengthen the author's argumentation, I would distinguish in their quantification between gal4+ from the other [classes of neighboring neurons]” (Fig. 2 and 4).”

    Our focus in this paper was to ask simply whether P1a neurons are active or not active during natural occurrences of the social behaviors they can evoke when artificially activated. We did not claim that they are the only cells in the region that control the behaviors. It is not possible to compare their activation to that of 'other' cells neighboring P1a neurons without a separate marker to identify those cells driven by a different reporter system (e.g., LexA). This in turn would require repeating all of the experiments in Figs 2 and 4 from scratch with new genotypes permitting dual-labeling of the two populations by different XFPs, and quantifying the data using 4-color labeling. We respectfully submit that such curiosity-driven experiments, while in principle interesting, are beyond the scope of the present manuscript. However, we have inserted text to acknowledge the possibility that the aggression-activated Hr38 signals in P1a- cells neighboring P1a+ cells may correspond to other classes of P1 neurons (of which there are 70 in total) or to pC1 cells. Changes: Text lines 151-154.

    “if the magenta dot is outside of the nuclei I would not count this as positive also the size of the dot seems to be a good marker of the reality of the signal). I would measure the intensity of the hr38EXN. A high Hr38EXN level associated with the presence of hr38INT would indicate that the cell has been activated during both encounters, while a lower hr38EXN with no hr38INT would suggest only an activation during the 1st behavioural context. Finally, a lower hr38EXN associated with the presence of hr38INT would suggest the opposite, an activation only during the 2nd behaviour.”

    We agree that there are some tiny dot signals with hr38 INT probe that are more likely the background signals. We only counted the INT probe signals as positive when the cells had a clearly visible dot and also co-localize with the exonic probe's signal, as primary (un-spliced) Hr38 transcripts in the nucleus should be positive for both EXN and INT probes. Regarding the reviewer’s latter comments, we agree with their interpretation of the catFISH results and that is how we interpreted them originally. We measured the intensity of hr38EXN expression and defined hr38EXN-labeled cells as “positive” when the relative intensity was 3σ >average, a stringent criterion. In the revised manuscript, we added more detailed information in the methods section regarding our criteria for defining cell types as positive.

    “Knowing that the P1a neurons (using the split-gal4) can trigger only wing extension when activated by optogenetic 50Hz, I would test to which behavioral context the MB neurons and the PAM neurons positively respond to.”

    As we answered in 'Response to Public Review,' our opto-HI-FISH experiments identified Kenyon cells in the mushroom body (MB) and PAM neurons (as well as pCd neurons) as potential downstream targets of P1a cells, using Hr38 labeling. The purpose of the calcium imaging experiment in Figure 3 – supplement was to confirm the P1a-dependent activation of KCs and PAM neurons using an independent method. In that respect this control experiment was successful in that methodological confirmation. The reviser raised an interesting question about how our calcium imaging experiments relate to our behavioral experiments, in terms of the dynamics of KC and PAM activation. A recent publication (Shen et al., 2023) revealed that courtship behavior has a positive valence and that activation of P1 neurons mimics a courtship-reward state via activation of PAM dopaminergic neurons. Therefore, it is reasonable to think that PAM neurons (and Kenyon cells as downstream of PAM neurons) are activated during female exposure. However those data do not exclude the possibility that inter-male aggression is also rewarding in Drosophila males, as it has shown to be in mice. This is an interesting curiosity-driven question that has yet to be resolved. Therefore, as mentioned in the 'Response to Public Review,' we feel that the additional experiment the reviewer suggests is beyond the scope of our manuscript.

    Changes: None.

    Minor comments:

    “Please provide different pictures from main fig2 and sup2 for the three common conditions (control, aggression, and courtship).”

    The data set for Figure 2 and Figure 2 supplement are from the same experiment. Because of the limited space, we just presented the selected key conditions ('Control', 'Aggression', and 'Courtship') in the main figure and put the complete data set (including these three key conditions) in the supplemental figure.

    Changes: None

    “Please, provide scale bars for the images.”

    Also, Reviewer #2 commented, 'Scale bars are missing on all the images throughout the main and supplementary figures.'

    We have now added scale bars for each figure.

    “Fig.1: “Is the chrimsonTdtom images from endogenous fluorescence? It is not said in the legend and anti-dsred is not provided in the material and method while anti-GFP is.”

    We are sorry for the confusion and thank the reviewer for raising that question. The signals were native fluorescence, and we have now added that information to the figure legend.

    P7: "As an initial proof-of-concept application of HI-FISH, we asked whether neuronal subsets initially identified in functional screens for aggression-promoting neurons (Asahina et al., 2014; Hoopfer et al., 2015; Watanabe et al., 2017) were actually active during natural aggressive behavior. These included P1a, Tachykinin-FruM+ (TkFruM), and aSP2 neurons". Please put the references to the corresponding group of neurons listed. For example: "These included P1a neurons [Hoopfer et al., 2015]".

    We have now added these references.

    P9: "Optogenetic and thermogenetic stimulation experiments have shown that that P1a interneurons can promote both male-directed aggression and male- or female-directed courtship" typo

    We appreciate the reviewer for catching this error and have corrected the text.

    (P10:" To validate this approach, we first asked whether we could detect Hr38 induction in pCd neurons, which were previously shown by calcium imaging to be (indirect) targets of P1a neurons". Reference [Jung et al., 2020]

    We have now added this reference.

    Fig. 4A: Put the time scale on the diagram (3h adaptation-20min-30min rest-20min-10min rest-collect)

    We have now added the time scale in Figure 4A.

    Reviewer #2:

    Response to Public Review:

    We thank the reviewer for their helpful comments and suggestions. We have addressed most of them in our revised manuscript. The main concern of Reviewer #2 was the temporal resolution of the HI-catFISH experiment shown in Figure 4 and Figure 4-Supplement. Our original manuscript illustrated temporal patterns of Hr38EXN and Hr38ITN signals concomitant with different behavioral paradigms (Figure 4B). The reviewer pointed out that the illustrated experimental design does not reflect the actual data shown in Figure 4-Supplement A-C. We believe this issue was raised because we drew the temporal pattern of Hr38EXN signals in Figure 4B based on the intensity of Hr38EXN signals (Figure 4-Supplement B) rather than based on the % number of positive cells (Figure 4-Supplement C). We have now revised the schematic time course of Hr38EXN signals in Figure 4B using the % of positive cells. We believe this change will be helpful for readers to understand better the experimental design since we used the % of positive cells to identify patterns of P1a neuron activation during male-male vs. male-female social interactions in Figure 4D. Another suggestion from Reviewer #2 was to add additional controls, such as the quantification of the intronic and exonic Hr38 probes after either only the first or second social context exposure. In response, we have now added the data from only the first social context (Figure 4C, and 4D, right column). These new data provides evidence that there are essentially no detectable Hr38INT signals 60 minutes later without a second behavioral context, while Hr38EXN signals are still present at the time of the analysis. Unfortunately, we are not able to provide the converse dataset with the second behavioral context only to show that Hr38 INT signals are detected. On this point, we call the reviewer’s attention to Figure 4-supplement-S4A-C, which show that the INT probe signals are detectable at 15 and 30 minutes following stimulation, but not at 60 minutes. In the experiment of Fig. 4B, flies are fixed and labeled for Hr38 30 minutes after the beginning of the second behavior, conditions under which we should obtain robust INT signals (as observed). EXN signals are also expected at 30 minutes because the primary (non-spliced) RNA transcript detected by the INT probe also contains exonic sequences.

    Response to Recommendations for the authors:

    Given that the development of in situ HCR for the adult fly brain is so central to the present manuscript, I think that the methods section describing the HCR protocol can be significantly improved. In particular, the authors should fully describe the in situ HCR protocol including the 'minor modifications' they refer to, and define how they calculate the 'relative intensity to the background'.

    We appreciate the reviewer’s suggestion. We have now revised the methods section to describe the procedure in more detail. Also, we will submit a separate document describing the HI-FISH protocol.

    Note: The authors refer to a recently published paper by Takayanagi-Kiya et al (2023) describing activity-based neuronal labeling using a different immediate early gene, stripe/egr-1. The authors state the following: 'That study used a GAL4 driver for the stripe/egr-1 gene to label and functionally manipulate activated neurons. In contrast, our approach is based purely on detecting expression of the IEG mRNA using..'. Takayanagi-Kiya et al. (2023) also use in situ mRNA detection of the IEG stripe/egr-1 and not only a GAL4 driver system. This claim should be modified and the paper should be cited in the introduction of the present paper.

    We have now cited the paper in the Introduction and have modified and moved the description originally in 'Note' section to Discussion (text lines: 392-404) as the reviewer requested. We have emphasized the difference between the two approaches for comparing neuronal activities during two different behaviors within the same animal. Takayanagi-Kiya used GAL4/UAS and stripe protein expression with immunohistochemistry to analyze neuronal activities during two different behaviors, while we exclusively analyzed Hr38 mRNA expression for this purpose, using intronic and exonic Hr38 probes. This approach made it possible to perform catFISH with higher temporal resolution and also allows extension of our approach to other IEGs for which antibodies are not available.

    Please specify the nature of the iron fillings in the methods section.

    We added a detailed description in the methods section, including the catalog number.

    In Figure 1B, the authors may add a dashed outline to the regions magnified in 1C so that readers can more easily follow the figures. Moreover, it would be informative to see a more detailed quantification of the number of Hr38-positive cells in different brain regions marked by Fru-GAL4.

    We have now added the whole brain images for each condition in Figure 1C and also quantitative data in Figure 1-Supplement C, as the reviewer suggested.

    In the middle right aggression panel of Figure 2A, it looks as if one P1a neuron is not outlined.

    We have carefully examined other z-planes through this region and based on those data have concluded that the signals mentioned by the reviewer are neurites from neurons labeled in other z-planes.

    Changes: None.

    The images in Figure 2A can be again found in Figure Supplement 2A, yet the number of neurons analyzed suggests the quantification was performed from different samples. The images in Figure Supplement 2A should be either changed or it should be explained as to why the images are the same yet the numbers in the legend are different.

    We apologize for the confusion. Figure 2 and Figure 2-Supplement are from the same experiment. To avoid clutter we illustrated three key conditions ('Control,' 'Aggression,' and 'Courtship') in the main figure. The reason why the numbers in the legend are different is that the purpose of presenting Figure 2-Supplement B-D was to determine whether there were differences in the intensity of Hr38 FISH signals in the neurons considered as 'positive' in different conditions. Therefore, the numbers described in Figure 2-Supplement legend are derived only from those neurons that were considered Hr38-positive, while the numbers in Figure 2 include all neurons analyzed. We have now added notes to explain this in the Figure 2 – supplement legend.

    The panels of the quantification of the Hr38 relative intensity in Figure 2B/C/D are very difficult to read, ideally, they should be plotted as in Figure Supplement 2B/C/D.

    The graphs in Figure 2B-D (upper) show data from all GFP-labeled cells scored, including cells defined as 'negative' or 'borderline.' In contrast, the graphs in Figure 2-supplement show the relative Hr38 signal intensity in those GFP neurons defined as positive based on the analysis in Fig. 2B. If we were to plot the data in Fig. 2B (upper) as box plots (like that in Figure-2-supplement), we would see either a skewed (only negative cells) or a bimodal distribution (one around the negative population and the other around the positive population); the shapes of these distributions would likely be hidden in the box-whisker plots format. Therefore, we prefer to plot all of the data points as we did in the original manuscript. However, we agree that the data points in the original manuscript were hard to read. We therefore changed the format of the datapoints from blurry dots to open circles with clear solid lines.

    In Figure 2B/C/D, please specify in the figure legend what 'grouped in categories according to character' means.

    We used letters to mark statistically significant differences (or lack thereof) between conditions. Bars sharing at least one common letter are not significantly different. If they do not share any letter, they are significantly different. For example, Aggression: bc vs. Dead: bc, means no difference. Aggression: bc vs. No Food: b, or Aggression: bc vs. Courtship: c also means no difference between Aggression and each of the two other conditions. However, 'No Food: b' and 'Courtship: c' have no common letter, meaning they are different. This is a standard method for showing statistically comparisons among multiple bars without lots of asterisks and horizontal bars cluttering the figure, and we have revised the legend to clarify what each letter means. We have also removed the color shading in Figure 2 B-D as it may have been confusing.

    A quantification of the number of Hr38-positive neurons and Hr38 relative intensity during the entire time course would be informative in Figure 3D.

    Although the data set for this figure is different from that for Figure 4-Supplement A-C, the main claim is the same. Therefore, Figure 4 - Supplement essentially provides the information that the reviewer suggested. However, we also reanalyzed the data set used for the original Figure 3D and evaluated % positive cells at the 30-minute time point and have now added that number in the figure legend.

    In the legend of Figure 3D, it says '..The expression level reaches its peak at 30-60min', yet I don't see timepoints beyond 60min. Please rephrase or add additional timepoints.

    We apologize for the error. We have rephrased the text.

    Figure Supplement 3A/D: please add an outline or a schematic figure to better understand where the imaging is performed.

    We added illustrated schemas next to the title of each experiment (P1->PAM neurons (bundle) and P1 -> Kenyon cells (bundle)).

    Figure Supplement 3C/F: please add information about the statistical test to the corresponding figure legend.

    We have added a phrase to describe the test used.

    Figure Supplement 3G/H/I/J: motion artifacts can potentially strongly affect the performed analysis given that cell bodies are very small and highly subjected to motion. Can the authors comment on how they corrected for motion?

    We have now described how we corrected for motion artifacts in the Methods section.

    Figure 4C/D: It seems as if the representative images don't reflect the quantification, e.g., in the male -> female panel, close to 100% of the neurons are positive for the exonic probe as opposed to approx. 40% in the bar graph.

    Please see our response to this issue in the 'Response to Public Review (Reviewer #1)'.

    Additional controls should be included in Figure 4C in order to assess the temporal resolution of HI-CatFISH more in detail (see 'Weaknesses').

    We have also answered this in the 'Response to Public Review'.

    The authors should adjust the scheme in the main Figure 4B to reflect the data presented in Figure S4A and C. For instance, the peak for the intronic version is observed at 15 minutes, while at 30 minutes, both the exonic and intronic signals show an equal level of signal.

    We have addressed this issue in the 'Response to Public Review'.

    We thank the reviewers again for their helpful comments and hope that with these changes, the manuscript will now be acceptable for official publication in eLife.

  7. Version published to 10.1101/2023.09.28.560045v2 on bioRxiv
  8. Version published to 10.7554/elife.92380.1 on eLife
  9. eLife

    Author Response

    1. Reviewer 1 raised the concern that the images shown in the figures seem inconsistent with the quantitative data.

    Our provisional response: The quantitative data are based on many samples and the photographs are just supposed to show illustrations of example data. Because of the volume containing P1a cells, is impossible to present a single confocal image that covers all P1a neurons and would therefore correspond more closely to the quantitative data. We chose to illustrate the quantitative data using single confocal images which contain both Hr38+/GFP+ and Hr38-/GFP+ neurons, to demonstate that we can distinguish clearly which P1a neurons are positive or negative for for Hr38 expression. This can be clarified in the figure legends. If it is imperative to show images(s) to reflect the statistics, we can do that but will need to present multiple confocal images for each condition, which could be messy and confusing.

    1. Reviewer 2 states: "the major weakness is the calibration of the temporal resolution of HI-CatFISH in Figure 4 and Figure Supplement 4. According to Figure Supplement 4C, close to 100% of the Hr38-positive cells are already labeled with the exonic probe 30min post-stimulation, which is not reflected in Figure 4B (there, the expression level of the exonic probe peaks 60min post-induction)”.

    The confusion may arise because we drew the illustration diagram (Fig. 4B) based on the quantitative data in Fig.S4B, which plots the intensity of Hr38 exonic ISH signals, while the reviewer may be comparing the illustration to the time course based on Fig.S4C, which shows the % positive cells, a binary measure. In the illustration (fig.4B), we wrote 'Hr38 expression level', not '%Hr38 positive cells.’ We can clarify this in the figure legend. If the reviewers prefer, we can add a threshold line in the diagram corresponding to the % positive cells at maximum.

  10. eLife

    eLife assessment

    The work addresses an important methodological aspect by optimizing an activity-dependent labelling of neural circuits in behaving flies. The authors provide convincing evidence to support the broad applicability of this method. However, a more comprehensive description of the methodology would greatly enhance its dissemination and adoption. Additionally, the authors successfully implement the method, providing solid evidence for the activity-dependent labelling of P1 neurons during aggression and courtship.

  11. eLife

    Reviewer #1 (Public Review):

    Summary:
    The authors have nicely demonstrated the efficiency of the HCR v.3.0 using hr38 mRNA expression as a marker of neuronal activity. This is very important in the Drosophila neuroscience field as in situ hybridization in adult Drosophila brains has been so far very challenging to do and replicate. However, this method has been described before [Choi et al., (2018)] and, if I understand correctly, is now the property of the non-profit organization molecular Technologies, who are the ones responsible for designing the probes (the sequences are not provided). Here the authors present their work as a description of a new method, called HI-FISH. However, I do not consider this as a new method but rather an application, a "proof of principle" that HCR v.3.0 can be done even on challenging tissues such as the adult Drosophila brain. Hence, if HCR v3.0 is sensitive enough and powerful enough to be used as a marker of neuronal activity, we can use it, for other neurobiological purposes, using other gene probes.
    To demonstrate the efficiency of HI-FISH, the authors have addressed two biological questions. The first one addressed whether specific groups of neurons, known to trigger specific behaviours (here courtship and/or aggression) are indeed activated by the behavioural context they can promote. In other words: is the behavioural output of these neurons also a trigger for their activation? The second question addressed whether this method is powerful enough to distinguish two subgroups of a class of neurons called P1 known to be involved in the two behaviours considered. In other words, are the same P1 neurons that promote aggression and courtship?

    Strengths: The demonstration of the efficiency of the method is very convincing and well-performed. It gives the will for the reader to apply the method to their own subject.

    Weakness: The pictures provided for HI-FISH and catFISH do not corroborate with the quantification and therefore I am not convinced about the author's biological interpretation of their data. See below for details.

    Previously, using a split-gal4 line to restrict the Gal4 expression to a subset of P1 neurons, the authors have shown that these particular neurons when activated can trigger both aggressivity and courtship behaviour [Hoopfer et al., 2015]. The P1 neurons are composed of about 20 FruM neurons/hemibrain but are part of a bigger group that comprises about the same number of Fru- neurons that seem to be exclusively aggression-promoting neurons [Koganezawa et al., 2016]. Hence, this group of 40 neurons (pC1 neurons) contains aggressive-promoting neurons, courtship-promoting neurons, and perhaps neurons that can do both. Therefore, to address the first question, the authors compared hr38 expression in different groups of neurons, with a focus on subgroups, under different social contexts. While there is no ambiguity concerning the function of the Tk neurons as being exclusively aggressive-promoting neurons [Asahina et al., 2014], it is less clear when we look at the pC1 neurons. This is particularly evident for the P1a neurons which have been shown to be ambiguous as they can promote both aggression and courtship. For example, while optogenetic activation of these neurons promotes hr38 expression (Fig. 3D and fig sup. 4), it is less clear in the pictures to determine whether these specific P1a neurons labeled by the split-gal4 line are specifically activated by an aggressive behavioural context or a courtship behavioural context (Fig1, supp. 2 and fig. 4). Furthermore, the pictures chosen do not reflect the reality of the quantification (Fig. 2 B-D compared to sup. 2 or fig. 4C compared to fig. 4D) and therefore the authors conclusion. Because the drivers used are only expressed by a small subset of a larger population, I believe it would be more informative to separate in the quantification between the Gal4-expressing neurons and the non-expressing ones. Notably, based on the pictures provided, it looks like more P1 neurons (or rather pC1 neurons) are activated by a male-male encounter than by a male-female encounter. On the other hand, the splitGal4+ P1a seem to be more responsive to a courtship behavioural context (2/6 P1a neurons express hr38 in a courtship behavioural context while 0/9 _if we mentally abstract the increase of the background signal compared to the control picture_ seem to express hr38 in an aggression behavioural context). Hence, while activation of this P1asplit-Gal4 can promote both aggressive behaviour and courtship behaviour [Hoopfer et al., 2015], the authors didn't provide clear evidence (pictures not corroborating the quantification) that these specific small subpopulation of neurons are activated by one or the other or both behavioural conditions. Therefore my suggestion of differentiating in the quantification between the Gal4+ neurons from the others in the same local area.

    Fig. 3, suppl. 3: In this section the authors addressed the question of whether the HI-FISH can be used to identify the downstream targets of this subpopulation. As positive controls of known downstream targets, the authors looked at the pCd population which they recently published as being an indirect downstream target of the P1a neurons [Jung et al., Neuron 2020]. They identified the Kenyon cells and a group of dopaminergic neurons, the PAM neurons as being activated by the P1a neurons. To confirm the increase of hr38 expression is indeed the result of a neuronal response of these neurons to the P1a activation, the authors used a different strategy used by them and others before. Using Gcamp signal to monitor the neuronal response of the presumably downstream targets the authors activated the P1a neurons using optogenetic (chrimson). It is important to note that they have previously shown that depending on the frequency of the light pulses activation of the P1a neurons can trigger only aggression, both aggression and wing extension or only wing extension [Hoopfer et al., eLife 2015]. Here the authors use 50Hz which is a frequency that leads to wing extension during the stimulation and aggressive behaviour at the offset of the stimulus [Hoopfer et al., eLife 2015]. Interestingly, the Gcamp experiment shows activation of the Kenyon cells and the PAM neurons but this activity is not maintained when the stimulus is turned off, suggesting that these neurons are activated during a courtship context rather than an aggressive behavioural context. I think it would be nice to see in which behavioural context the Kenyon cells and PAM neurons are activated (hr38 expression in the different behavioural context using the corresponding Gal4).
    Fig.4 and supp.4: The demonstration that the catFISH can now be done in Drosophila brain with a new in situ method was nicely performed. Notably, the intronic Hr38 probe appears to be an excellent marker for recent neuronal activation. However, while the optogenetic activation of the P1a neurons used to quantify the time lapse for both probes nicely distinguishes between nuclear and cytoplasmic exonic hr38, it is very difficult to use the localization of this probe in the experimental setup the authors used. Also, With their setup, I would simply use the frequency of intronic hr38 as a marker of recent activation correlating or not with the frequency of exonic hr38 marker (present in both conditions first and second encounter). This is important as this experiment addresses the second biological question. Once again, the pictures chosen absolutely do not corroborate the quantification. For example, the picture of the double encounter with the same gender male-male context clearly shows a higher number of cells that are hr38INT positive (and therefore nuclear) than the picture of the female-female context (Fig. 4C), and thus even if we only considered the P1asplit-Gal4 positive cells. In the male-male picture, 5/6 P1a cells have the Hr38INT marker while the presence of this marker is debatable in the female-female context. Especially, in some of the cells these magenta dots appear to be localized in the cytoplasm, suggesting a non-specific signal. Therefore, I would suggest to quantify the percentage of Hr38INT positive cells as the only marker for recent activation and the relative level of Hr38EXN immunostaining, and this among the P1asplit-Gal4 positive cells and the gal4- ones. A high Hr38EXN level associated with the presence of hr38INT would indicate that the cell has been activated during both encounters, while a lower hr38EXN with no hr38INT would suggest only an activation during the 1st behavioural context. Finally, a lower hr38EXN associated with the presence of hr38INT would suggest the opposite, an activation only during the 2nd behaviour.
    Overall, by only looking at the pictures provided, I would conclude that the HCR applied with the hr38 probes seems to efficiently work and is usable to address the question of whether a specific group of neurons are indeed activated by a specific social behavioural context. However, I would also conclude that this technique nicely demonstrated that flies are not robots and that even in a "simple" organism model such as Drosophila melanogaster individual variability is present among a group of neurons. Hence, only the quantification of the gal4-expressing neurons in comparison with their neighbor neurons known to belong to the same functional group, would allow a conclusion toward a specificity of contextual response. Therefore, although activation of a small group of neurons can be enough to trigger a specific behaviour that shouldn't happen under a certain environmental context [Hoopfer et al., eLife 2015], the results presented here suggest that we should, using this method, considering the response of the neighbour cells of the Gal4+ ones. Although currently, the quantification of the author's data does not allow such analysis, to strengthen the author's argumentation, I would distinguish in their quantification between gal4+ from the others (Fig. 2 and 4). Furthermore, I am not certain that the distinction between cytoplasmic and nuclear hr38EXN is 100% feasible (based on the pictures provided). I would instead for the hr38EXN marker only use the relative intensity (Fig. 4D).

  12. eLife

    Reviewer #2 (Public Review):

    Summary:
    Watanabe et al establish a novel method for the activity-dependent labeling of neural circuits in flies. While activity mapping of neurons that are active during specific behaviors is widespread in rodents, the application of this method to fly circuit neuroscience is limited, mainly due to technological challenges. Thus, the present study addresses a timely problem. To do so, they apply the in situ hybridization amplification method called Hybridization Chain Reaction v. 3.0 (Choi et al. 2018) to the adult fly brain in order to visualize the expression changes of the immediate early gene (IEG) Hr38 under different types of social contexts. The conclusions of this paper are mostly very well supported by data but it would strongly benefit from additional methodological details as well as additional controls, in particular for the HI-catFISH experiments.

    Strengths:
    The major strength of this method is its versatility and sensitivity. It can be applied to a wide variety of biological questions and assess the dynamic transcriptional regulation of an unlimited number of genes with a high signal-to-noise ratio. It will be therefore useful to many research labs working on different biological questions.

    Weaknesses:
    Although the paper has great strengths in principle, the major weakness is the calibration of the temporal resolution of HI-CatFISH in Figure 4 and Figure Supplement 4. According to Figure Supplement 4C, close to 100% of the Hr38-positive cells are already labeled with the exonic probe 30min post-stimulation, which is not reflected in Figure 4B (there, the expression level of the exonic probe peaks 60min post-induction) and may have profound implications for the interpretation of the results. The present manuscript would strongly benefit from additional controls, such as the quantification of the intronic and exonic Hr38 probes after either only the 1st or 2nd social context but at the same timepoint than if two consecutive social contexts were tested.

  13. Version published to 10.1101/2023.09.28.560045v1 on bioRxiv