Drosophila can be used to achieve OPP labeling of newly-synthesized proteins in targeted cell populations within the brain. Following a brief 2 hr incubation of intact brains with PhAc-OPP, we observe robust imaging and affinity purification of OPP-labeled nascent proteins in PGA-targeted cell populations. We apply this method to show a pronounced age-related decline in neuronal protein synthesis in the fly brain, demonstrating the capability of PhAc-OPP to quantitatively capture in vivo protein synthesis states. This method, which we call POPPi (PGA-dependent OPP incorporation), should be applicable for rapidly visualizing protein synthesis and identifying nascent proteins synthesized under diverse physiological and pathological conditions with cellular specificity in vivo.Controlled protein synthesis is required to regulate gene expression and is often carried out in a cell type-specific manner. Protein synthesis is commonly measured by labeling the nascent proteome with amino acid analogs or isotope-containing amino acids. These methods have been difficult to implement in vivo as they require lengthy amino acid replacement procedures. O-propargyl-puromycin (OPP) is a puromycin analog that incorporates into nascent polypeptide chains. Through its terminal alkyne, OPP can be conjugated to a fluorophore-azide for directly visualizing nascent protein synthesis, or to a biotin-azide for capture and identification of newly-synthesized proteins. To achieve cell type-specific OPP incorporation, we developed phenylacetyl-OPP (PhAc-OPP), a puromycin analog harboring an enzyme-labile blocking group that can be removed by penicillin G acylase (PGA). Here, we show that cell type-specific PGA expression in  Controlled protein synthesis plays a fundamental role in orchestrating gene expression, and cellular protein amounts are thought to be primarily determined at the level of translation . TranslaDespite advances in assessing the transcriptome with cellular resolution, mRNA levels are an imprecise surrogate for protein abundance, and methods to capture the nascent proteome of individual cell populations in vivo have lagged behind. Current methods employ indiscriminate protein synthesis labeling in all cells of a tissue followed by flow sorting of tagged cell suspensions from these tissues  or regioE. coli enzyme PGA  followed by click-chemistry conjugation to either a fluorophore-azide for protein visualization or a biotin-azide for protein capture  in PhAcAs observed upon treating brain explants with OPP , we findUAS-PGA flies to pan-neuronal, pan-glial, or ubiquitous GAL4 driver strains and assessed the resulting progeny. Startle-induced negative geotaxis behavior is dependent on a functionally-intact nervous system and declines progressively with age in flies  flies of the same genotype  carbamate spacer which renders PhAc-OPP more hydrophobic than OP-puromycin. This is anticipated to enhance the ability of PhAc-OPP to penetrate cell membranes by diffusion, while diluted concentrations can still be prepared in an aqueous solution for tissue incubation .Spatially-resolved proteomic studies have lagged behind transcriptomic studies in part because issues with limited RNA starting material can be overcome by PCR amplification of cDNA, while no equivalent exists for protein. Nonetheless, flies can be rapidly bred to vast numbers and we anticipate that the facile scalability of l brains  as well l brains . Accordielopment , functioelopment , aging  under the same conditions used for protein synthesis labeling in the brain . We alsoCurrent proteomic approaches for measuring protein synthesis harbor strengths and weaknesses compared to transcriptomic approaches. Ribosomal profiling and other ribosome capture methods such as TRAP measure ribosomal density on a given transcript which provides a proxy for the rate of protein synthesis but not an actual measure of protein product. Ribosomal profiling has provided important insights into mechanisms of translational control, yet, there are some weaknesses to the method . PerhapsDrosophila brain. We believe this method will be a powerful tool for studying the role of the proteome and translational control in nervous system function with cellular resolution.In summary, we provide a new labeling method for rapidly visualizing, capturing, and quantifying cell type-specific nascent proteomes within the UAS-PGA and GAL4 into Drosophila S2 cells, the construct was microinjected into w1118 fly embryos . Transgenic FLAG-PGA expression was confirmed by FLAG Western blotting of adult head extracts after crossing all generated UAS-PGA lines to Actin5C-GAL4 (ubiquitous), elavC155-GAL4 , and repo-GAL4 . The following strongest-expressing lines were used throughout the study: UAS-PGA-1 for ubiquitous expression and UAS-PGA-3 for neuronal or glial expression. The repo-GAL4, UAS-mCD8::mCherry recombinant line was a gift from M. Freeman and all other lines were obtained from the Bloomington Drosophila Stock Center: TH-GAL4 (line 8848); C155-GAL4elav (line 458); repo-GAL4 (line 7415); Act5c-GAL4 (line 25374). All flies were reared and aged at 25 °C/60% relative humidity under a 12 hr light-dark cycle on a standard food medium.PGA-expressing flies were generated by subcloning N-terminal FLAG-tagged full-length PGA cDNA (gift of C. Doe) into the fly transformation vector pUAST between KpnI and EcoRI restriction sites. After sequence verification and successful construct expression following transient transfection of PhAc-OPP was synthesized from chemical precursors, analyzed by proton NMR, analytical thin-layer chromatography, and purified by flash chromatography as previously described .Drosophila medium (with L-glutamine and sodium bicarbonate), bath sonicated for 6 min, vortexed continuously for 30 s prior to adding the proteasomal inhibitor MG132 (60 μM) and then kept at RT until use. To prepare PhAc-OPP for ingestion in a small food volume, 2 X the final desired concentration of PhAc-OPP was dissolved in 0.25 ml of distilled water via several brief tip sonication pulses, briefly heated to 55 °C then mixed thoroughly in a 1:1 volumetric ratio with 0.25 ml of 2 X sugar-yeast food solution (3% agar/10% sucrose/20% yeast extract) previously heated to 100 °C and cooled to 55 °C. After the food had solidifed, the microfuge tube containing the food was cut just above the food surface and inserted upright into a cotton plug placed at the bottom of a shell vial. Flies were transferred to the vial and kept in a humidified chamber throughout feeding for the indicated durations.To prepare PhAc-OPP for tissue incubations, a stock solution (20 mM dissolved in DMSO) was diluted to 100 μM in Schneider’s Drosophila medium (formulated for Drosophila cells and tissues and supplemented with L-glutamine and sodium bicarbonate), based on previously reported methods (Drosophila CNS explants has often included the addition of insulin and/or serum to the culture medium (35S-methionine/cysteine (2 mCi/ml) to metabolically label newly-synthesized protein. Brains were incubated for 30 min at 25 °C with gentle orbital shaking, washed twice in 1 ml of PBS then flash frozen. Brains were homogenized in modified RIPA extraction buffer  on ice using a pestle gun. After a 30 min incubation on ice, lysates were centrifuged at 14,000 × g for 15 min and the supernatant was retained. Protein was precipitated by the addition of methanol and heparin (lysate:heparin (100 mg/ml):methanol volume ratio of 150:1.5:600), centrifuged at 14,000 × g for 2 min, the supernatant was removed, and the pellet was air dried. The protein pellet was resuspended in 8 M urea/150 mM Tris, pH 8.5, and 35S-methionine/cysteine incorporation was measured by liquid scintillation counting  and normalized to the number of brains.Adult brains were isolated and maintained for protein synthesis assessment in Schneider’s  methods . Prior le medium . As globe medium  and as i1118w were harvested in Schneider’s medium and transferred to Schneider’s medium containing 35S-methionine/cysteine (2 mCi/ml) and PhAc-OPP at the indicated concentrations. Brains were incubated for 2 hr at 25 °C with gentle orbital shaking, washed twice in 1 ml of PBS then flash frozen. Thawed brains were homogenized and processed for protein precipitation and measurement of 35S incorporation by scintillation counting as described above.Adult fly brains (8–10 per genotype) from the standard laboratory control strain Drosophila brain explants maintained in Schneider’s Drosophila medium were incubated with OPP or PhAc-OPP within 30 min of collection (‘newly-isolated brains’). Brains  were harvested in Schneider’s medium and then immediately transferred to Schneider’s medium containing OPP (50 μM unless otherwise indicated) or PhAc-OPP (100 μM unless otherwise indicated) and MG-132 (60 μM) for 2 hr (unless otherwise indicated) at 25 °C with gentle orbital shaking. Brains were washed twice briefly in 1 ml PBS and then immediately processed for immunocytochemistry or enrichment and immunoblot detection as described below.To enable rapid labeling of nascent CNS proteins, adult 2O, AF488-azide detection and subsequently total protein visualization using colloidal blue stain.OP-puromycylated tissues were fixed for 20 min in 4% paraformaldehyde in PBS-T  at RT with gentle rocking, washed once in chilled PBS-T (5 min) and once in chilled PBS (5 min). Detection of OP-puromycylated protein was achieved by conjugation to a fluorophore-azide called AF488 picolyl azide (AF488-azide) via CuAAC click reaction. A click working reagent was prepared containing TBTA (200 μM), freshly prepared Cu(I)Br (0.5 mg/ml), AF488-azide (0.1 X concentration), and 1 X concentration OPP reaction buffer (the last two reagents derived from the Click-iT Plus OPP Alexa Fluor 488 Protein Synthesis Assay Kit (Invitrogen) and at concentrations relative to those recommended in the manufacturer’s instructions). The click working reagent was vortexed for 30 s then applied to brains and incubated for 30 min at 25 °C with gentle orbital shaking and protection from light. Tissues were washed briefly with 1 ml of Click-iT Reaction Rinse Buffer and either whole-mounted or additionally counterstained with Dylight Phalloidin-650 or immunostained for cell markers or DAPI stained prior to mounting. Tissues were imaged on a Zeiss LSM900 confocal microscope. For in-gel fluorescence assays, OPP/PhAc-OPP treated brains were lightly fixed (4% PFA/10 min), click-conjugated to AF488-azide as described above then lysed in de-crosslinking buffer (300 mM Tris-HCl/2% SDS/protease inhibitors) for 2 hr at 60 °C prior to SDS-PAGE, gel fixation (40% methanol/10% acetic acid), 30 min washing in ddHThe protocol is modified from Wandering L3 larvae were washed briefly in PBS and then inverted to expose bodily tissues to the surrounding solution for labeling. Inverted larval preps were immediately transferred to Schneider’s medium, then incubated with 100 μM PhAc-OPP and 60 μM MG-132 followed by PFA fixation and click conjugation to AF488-azide under the same conditions used for adult fly brains. Tissues targeted for imaging  were separated, counterstained with Dylight Phalloidin-650, and mounted for imaging on a Zeiss LSM 900 confocal microscope.Adult females  were collected under brief anesthesia and transferred to fresh food vials at 25 flies per vial. Flies were then transferred to fresh food vials every 3–4 days throughout the experiment and dead or censored (escaped or stuck in food) flies were counted during each transfer to fresh food.Cohorts of 75–100 female flies  were collected under brief anesthesia and transferred to fresh food vials to recover . Flies were aged for 6 weeks with transfer to fresh food twice per week. On the day of testing, flies were transferred to empty vials, allowed 1 min to rest and then tapped to the bottom of the vial three times within a 1 s interval to initiate climbing. The position of each fly was captured in a digital Blue dye  was added at 1.5% w/v to the food during preparation to measure food consumption as previously described . BrieflySamples were electrophoresed on 4–20% Tris-Glycine gradient gels and transferred to nitrocellulose membrane for immunoblotting using the following antibodies:From the Developmental Studies Hybridoma Bank: Brp (nc82) 1:50; Synapsin-1 (3C11) 1:500; Syntaxin (8C3) 1:500; Drpr (1:1 mix of 5D14:8A1) 1:400; Repo (8D12) 1:200. Other antibodies used were biotin (Bethyl Laboratories) 1:1000; FLAG (M2) (Sigma) 1:500; TH (Immunostar) 1:1000; Actin-HRP (Sigma) 1:1000; Ubiquitin (P4D1)  1:1000; GAPDH (GA1R) (ThermoFisher Scientific) 1:10,000.n), statistical tests , and Bonferroni post hoc analysis with associated p values. All statistical analyses were performed using GraphPad Prism except Log-rank (Mantel-Cox) tests for lifespan comparisons performed in SPSS.Quantified data are mean ± SEM and individual data points are plotted for data with n<10. Sample sizes for time-course experiments were determined based on evidence from pilot experiments. Statistical analysis details for each individual experiment are described in figure legends, including the number of flies or the number of groups of flies used  has been deposited at the Bloomington Drosophila Stock Center (stock ID pending) and will be shared upon request.Newly created  The authors developed a versatile labeling strategy to allow visualization and identification of newly synthesized proteins in a cell population of interest. The approach enables cell-specific nascent proteome labeling from brain tissues to examine the role of translational control in different physiological and pathological states. 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.Our editorial process produces two outputs: (i) Decision letter after peer review:Drosophila" for consideration by eLife. Your article has been reviewed by 3 peer reviewers, and the evaluation has been overseen by a Reviewing Editor and K VijayRaghavan as the Senior Editor. The reviewers have opted to remain anonymous.Thank you for submitting your article "Rapid Cell Type-Specific Nascent Proteome Labeling in The authors describe a potentially useful method to quantitatively identify and visualize the nascent proteome of individual cell populations. The characterization of the approach is incomplete and preliminary, and the method needs to be better validated.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. Test if PhAc-OPP penetrates into various non-brain dissected tissues, such as muscle, fat body, and trachea. Etc. This could be done in larvae by dissecting and inverting larvae, and exposing various tissues to the PhAc-OPP in solution.2. Test if ingested PhAc-OPP penetrates into the adult brain expressing elav>PGA.What are the pros/cons of this method versus currently available methods based on ribosome profiling? The sensitivity of this method would be good to comment on in comparison with existing methods. Also, when would this be the method of choice over other methods?3. How available are the reagents needed for POPPi, and are they easy to obtain by any research lab?4. The reagent AF488-azide is referred to differently in different places in the manuscript and was not well introduced or described.5. Because OPP incorporation is sequence-independent, it should be able to label and terminate a peptide chain at any amino acid residue. Therefore I would expect the western blot to show a wider band or a smear after OPP or POPPi labeling. However, all the blots shown in the paper show similarly sharp bands as in the corresponding controls. Can the authors provide an explanation? Are the shorter (incomplete) peptides being degraded very quickly?6. Many of the issues raised by reviewer 3 are important and should be addressed.In essence, the characterization of the method needs to be extended and validated.Reviewer #1 (Recommendations for the authors):To address my main criticism in the public review, I suggest the following experiments.1. Test if PhAc-OPP penetrates into various non-brain dissected tissues, such as muscle, fat body, and trachea. Etc. This could be done in larvae by dissecting and inverting larvae, and exposing various tissues to the PhAc-OPP in solution.2. Test if ingested PhAc-OPP penetrates into the adult brain expressing elav>PGA.Reviewer #2 (Recommendations for the authors):I would like the authors to address the following questions:What are the pros/cons of this method versus currently available methods based on ribosome profiling? The sensitivity of this method would be good to comment on in comparison with existing methods. Also, when would this be the method of choice over other methods?How available are the reagents needed for POPPi, and are they easy to obtain by any research lab?The reagent AF488-azide is referred to differently in different places in the manuscript and was not well introduced or described.Because OPP incorporation is sequence-independent, it should be able to label and terminate a peptide chain at any amino acid residue. Therefore I would expect the western blot to show a wider band or a smear after OPP or POPPi labeling. However, all the blots shown in the paper show similarly sharp bands as in the corresponding controls. Can the authors provide an explanation? Are the shorter (incomplete) peptides being degraded very quickly?Reviewer #3 (Recommendations for the authors):1. It is not clear what percentage of the newly synthesized polypeptides incorporate puromycin which would allow visualization or immunopurification of the protein through the use of azide conjugates. Since the inclusion of puromycin in the nascent peptide prevents further elongation of the nascent peptide, reaching the levels of puromycin to saturate the cells would likely be detrimental. On the other hand, when lower amounts of puromycin are used, it is likely that the lower expressed genes/polypeptides will not be labelled. In any case, the authors should estimate the ratio of the newly synthesized targeted by puromycin. This can be done by using PhAc-OPP in elav-Gal4 UAS-PGA brains in combination with azide-biotin and S35 methionine. This would allow immunopurification with an antibody specific for a protein (such as bruchpilot), measuring the level of S35, and a second immunopurification with streptavidin and measuring again with S35. This can allow the estimation of the percentage of newly synthesized proteins that are targeted by PhAc-OPP.2. It is not clear how there can be clear full-size bands in the Western blots in figure 3. The addition of PhAc-OPP should truncate the protein at random sites that correspond to where the OPP is added to the nascent peptide. This should result in smears in principle unless there is a tendency of OPP to get incorporated towards the end of the protein. An explanation should be included in the discussion to help the reader understand the data better. This also undermines the argument that the fact that there are bands of different sizes suggests that the proteome is uniformly targeted. Since puromycin addition truncates the gene products at random positions, the band sizes should not be informative and indicative of unbiased labelling of the proteome.3. Although the imaging using OPP and Alexa488-azide looks rather uniform labeling in figure 1C when PhAc-OPP is used in combination with elav-Gal4 or repo-Gal4 UAS-PGA, the Alexa488-azide signal is much more salt and pepper distributed in figure 2A and D . This is especially prominent in glia where very few of the mCherry expressing cells are labelled by Alexa488-azide in Figure 2D. This suggests that the proteome of some cells will be much higher represented in the samples when azide-biotin is used to immunopurified proteins expressed by a cell type, severely limiting the use of the technique.4. The fact that OPP-mediated labeling is quite uniform suggests that the translation levels do not change very much between cells and the reason for the non-uniform signal in figure2 may result from the non-uniform expression of UAS-PGA. The authors should stain the elav-Gal4 or repo-Gal4 UAS-PGA with an anti-Flag antibody to check for non-uniform expression of PGA.5. In figure 1 figure supplement 2B the authors should test incubation times that are between 0-2 hours better since at 2 hours the system already seems to be saturated.eLife.In summary, the technique needs to be better characterized to be more usable by the fly community. In addition, the demonstration experiments to show that there is an age-dependent decrease in translation rates are not the most informative demonstration of the use of the technique. Hence, this manuscript needs major revision and a better demonstration of the use of the technique to warrant publication in Drosophila" for further consideration by eLife. Your revised article has been evaluated by K VijayRaghavan (Senior Editor) and a Reviewing Editor.Thank you for resubmitting your work entitled "Rapid Cell Type-Specific Nascent Proteome Labeling in The manuscript has been improved but there are some remaining issues that need to be addressed, as outlined by the reviewer. It is really important to address these concerns in detail. Please can you do this at the earliest and submit a revised manuscript?Reviewer #1 (Recommendations for the authors):The authors satisfied the major concerns in my original review. However, I have an additional major concern.The data presented do not convince me that POPPi is a robust and useful method for capturing and identifying newly-synthesized proteins in a cell type-specific manner (e.g. w/ biotin-azide). In the response to my concern of my original review, the authors suggest that background bands seen in negative control lanes of western blots  are due to non-specific AF488-azide incorporation into all proteins (newly synthesized + old). This is unexpected to me, as I had assumed the click chemistry was specific to OPP-labeled proteins. Regardless, assuming that non-OPP-labeled proteins are labeled by AF488-azide, I interpret the western blots in Figure 4A and Figure 4C as showing weak 'signal above background'. This is especially concerning because Figure 4A,C were performed by labeling a large portion of the cells within the collected tissue (pan-neuron and pan-glia). So, labeling in smaller subsets of cell types (e.g. dopaminergic neurons) would be expected to result in even lower 'signal above background'. I outline below additional thoughts and suggestions that could help address my concerns.Recommendations for the authors:1. To more accurately assess the signal-to-background of cell type-specific labeled proteins, the authors should provide a proper negative control in Figure 4A and 4C. The "vehicle-only" negative control may underestimate the background levels of AF488-azide incorporation. I would argue that the most appropriate negative control is to incubate wild-type brains (e.g. elav>GFP) with PhAc-OPP. Hypothetically, PhAc-OPP could be uncaged by endogenous fly enzymes, which would result in higher background levels than the vehicle-only control. As far as I can tell, the possibility of uncaging PhAc-OPP without PGA is not discussed and remains untested in this manuscript. Furthermore, line 203 "PGA-dependent unblocking of PhAc-OPP…" is thus not supported by their data using the "vehicle-only" negative control in Figure 4. I suggest that the authors repeat the data in Figure 4A and 4C using the appropriate negative control I mentioned.Drosophila contains naturally biotinylated proteins, these new western blots would provide the fairest representation of signal-to-background. For example, naturally biotinylated proteins will bind to the streptavidin beads and thus be background on western blots and in Mass spectrometry (MS) data.2. The authors should provide western blots similar to Figures 4A,C, but using the biotin-azide labeling reagent. Since biotin-azide enables researchers to capture and detect OPP-labeled proteins using streptavidin-bead pulldown, it is critical that researchers understand the global signal-to-background when using this reagent. I suggest that the authors repeat Figure 4A,C using biotin-azide to label and streptavidin-fluorophore to detect. Furthermore, since 3. I would like to see MS data to support the data presented in Figure 4 B,D. These figures show that POPPi can enrich cell type-specific labeled proteins. However, the background bands for Synapsin, Syntaxin, and Draper are concerning and suggest the sensitivity of this method is low. To convince me that there is global signal over background, I would like to see MS analysis of samples in Figure 4B,D. For example, MS of streptavidin-pulldown from the following brain genotypes (1) elav>PGA + PhAc-OPP, (2) repo>PGA + PhAc-OPP, (3) elav>GFP + PhAc-OPP. Using quantitative approaches such as TMT labeling or SAINT analysis, I would expect to see enrichment of Draper to glia and Syntaxin to neurons, for example.Reviewer #2 (Recommendations for the authors):I'm generally satisfied with the responses and changes to the manuscript. My only remaining request is that the authors include a line for PhAc-OPP in the Key Resources Table. Clearly, this is a key reagent, and the authors should be transparent that it is something that needs to be synthesized, which will likely limit how widespread the method is used by the community. Essential revisions:1. Test if PhAc-OPP penetrates into various non-brain dissected tissues, such as muscle, fat body, and trachea. Etc. This could be done in larvae by dissecting and inverting larvae, and exposing various tissues to the PhAc-OPP in solution.Actin5C-Gal4 driver, and then immediately incubated inverted larvae in 100 µM PhAc-OPP for 2h under the same conditions as previously used for labeling brain tissue. Our prior results indicate robust PGA expression in larvae from this genotype . Upon dissecting and imaging individual tissues , we observed readily detectable protein synthesis labeling. This indicates that PhAc-OPP is able to penetrate a variety of tissues besides the brain to label newly-synthesized protein. These results are presented in the revised manuscript , Results (line 190), Discussion (line 367) and Methods (line 542).We thank the reviewer for suggesting this approach to assessing PhAc-OPP penetration into other tissues besides brain. We inverted L3 larvae expressing PGA via the 2. Test if ingested PhAc-OPP penetrates into the adult brain expressing elav>PGA.What are the pros/cons of this method versus currently available methods based on ribosome profiling? The sensitivity of this method would be good to comment on in comparison with existing methods. Also, when would this be the method of choice over other methods?elav-Gal4>UAS-PGA) to various concentrations of PhAc-OPP in sugar/yeast extract food for 48h then determined whether OPP-labeled nascent protein is detectable following AF488-azide conjugation. We observe concentration-dependent labeling with PhAc-OPP and AF488azide signal becomes significantly higher than background at concentrations ≥1 mM . Importantly, flies appear to consume 4 mM PhAc-OPP-containing food in similar quantities to that of control food , suggesting that food consumption is not significantly impaired by the presence of PhAc-OPP, even at the highest dose tested. These results suggest that PhAc-OPP administered dietarily can penetrate the brain at levels sufficient to obtain detectable albeit subtle nascent protein labeling. These results are described in the Results (line 265), Discussion (line 370) and Methods (line 438).To assess the feasibility of protein synthesis labeling via dietary PhAc-OPP intake, we exposed pan-neuronal PGA-expressing flies . Perhaps most importantly, inferring protein synthesis rates from a single snapshot of average ribosomal occupancy on a given mRNA is based on assumptions that all ribosomes complete translation, and are not subject to regulated translational pausing or abortion at the time of capture or at any time prior to finishing translation. Additionally, the method itself may miss ribosomal footprints if nuclease digestion is incomplete, and give rise to false readouts of translation from contaminating non-coding RNA fragments. In contrast, assessing translation at the level of synthesized protein, e.g. through quantitative proteomics, should avoid errors associated with inferring protein synthesis rates from ribosomal occupancy, with the caveat that sensitivity limits relative to transcriptomic approaches may make transcriptomics the method of choice when starting material is low. We believe a potential major advantage of POPPi over existing methods for measuring cell type-specific protein synthesis is its efficiency, particularly for visualizing protein synthesis – PhAc-OPP labeling coupled to AF488-azide conjugation can be completed within a few hours (see Methods). Future work will seek to understand the full capabilities and limitations of POPPi, e.g. for profiling rare cell populations in the brain.”3. How available are the reagents needed for POPPi, and are they easy to obtain by any research lab?PhAc-OPP is not currently commercially available, yet its chemical synthesis has been previously described in detail (Reference 12) which labs can use to have the compound synthesized, e.g. through a university chemistry core or a company. All other compounds used for the methods described are commercially available, including AF488-azide for visualizing protein synthesis and desthiobiotin-azide for enriching labeled protein. All reagent details are provided in the key resources table. PGA transgenic flies will be made available upon request, as indicated in the manuscript.4. The reagent AF488-azide is referred to differently in different places in the manuscript and was not well introduced or described.We now consistently refer to this reagent in its short form (AF488-azide) throughout the manuscript except when introducing the reagent in the Methods, where we added the statement “Detection of OP-puromycylated protein was achieved by conjugation to a fluorophore-azide called AF488 picolyl azide (AF488-azide) via CuAAC click reaction”. We regret the prior lack of clarity.5. Because OPP incorporation is sequence-independent, it should be able to label and terminate a peptide chain at any amino acid residue. Therefore I would expect the western blot to show a wider band or a smear after OPP or POPPi labeling. However, all the blots shown in the paper show similarly sharp bands as in the corresponding controls. Can the authors provide an explanation? Are the shorter (incomplete) peptides being degraded very quickly?It is likely that truncated proteins would be targeted for eventual degradation and depleted from the protein pool as the reviewer indicates. However, another simple explanation is that commercially available antibodies used for Brp, Synapsin and Draper are all reported to recognize epitopes at the C-terminal end of these proteins, which would be absent in most truncated protein and therefore not detectable on Western blot. The epitope for Syntaxin has not been mapped. Hence, the depletion of truncated proteins combined with an inability to detect them using the available antibodies used in this study likely explain their absence of western blots. We added this interpretation to the Discussion (line 337).6. Many of the issues raised by reviewer 3 are important and should be addressed.Please see our point-by-point response to reviewer 3 comments below.In essence, the characterization of the method needs to be extended and validated.Drosophila tissues besides the brain and (ii) label newly-synthesized protein in the brain when the labeling compound PhAc-OPP is administered to flies dietarily. We believe these revisions extend characterization of the method substantially.Our new findings presented in the revised manuscript support the capability of our method to (i) label newly-synthesized protein in Reviewer #1 (Recommendations for the authors):To address my main criticism in the public review, I suggest the following experiments.1. Test if PhAc-OPP penetrates into various non-brain dissected tissues, such as muscle, fat body, and trachea. Etc. This could be done in larvae by dissecting and inverting larvae, and exposing various tissues to the PhAc-OPP in solution.Actin5C-Gal4 driver, and then immediately incubated inverted larvae in 100 µM PhAc-OPP for 2h under the same conditions as previously used for labeling brain tissue. Our prior results indicate robust PGA expression in larvae from this genotype . Upon dissecting and imaging individual tissues , we observed readily detectable protein synthesis labeling. This indicates that PhAc-OPP is able to penetrate a variety of tissues besides the brain to label newly-synthesized protein. These results are presented in the revised manuscript , Results (line 190), Discussion (line 367) and Methods (line 542).We thank the reviewer for suggesting this approach to assessing PhAc-OPP penetration into other tissues besides brain. We inverted L3 larvae expressing PGA via the 2. Test if ingested PhAc-OPP penetrates into the adult brain expressing elav>PGA.elav-Gal4>UAS-PGA) to various concentrations of PhAc-OPP in sugar/yeast extract food for 48h then determined whether OPP-labeled nascent protein is detectable following AF488-azide conjugation. We observe concentration-dependent labeling with PhAc-OPP and AF488azide signal becomes significantly higher than background at concentrations ≥1 mM . Importantly, flies appear to consume 4 mM PhAc-OPP-containing food in similar quantities to that of control food , suggesting that food consumption is not significantly impaired by the presence of PhAc-OPP, even at the highest dose tested. These results suggest that PhAc-OPP administered dietarily can penetrate the brain at levels sufficient to obtain detectable albeit subtle nascent protein labeling. These results are described in the Results (line 265), Discussion (line 370) and Methods (line 438).To assess the feasibility of protein synthesis labeling via dietary PhAc-OPP intake, we exposed pan-neuronal PGA-expressing flies (Reviewer #2 (Recommendations for the authors):I would like the authors to address the following questions:What are the pros/cons of this method versus currently available methods based on ribosome profiling? The sensitivity of this method would be good to comment on in comparison with existing methods. Also, when would this be the method of choice over other methods?To address these questions, the following text has been added to the Discussion (line 386):“Current proteomic approaches for measuring protein synthesis harbor strengths and weaknesses compared to transcriptomic approaches. Ribosomal profiling and other ribosome capture methods such as TRAP measure ribosomal density on a given transcript which provides a proxy for the rate of protein synthesis but not an actual measure of protein product. Ribosomal profiling has provided important insights into mechanisms of translational control, yet, there are some weaknesses to the method (45). Perhaps most importantly, inferring protein synthesis rates from a single snapshot of average ribosomal occupancy on a given mRNA is based on assumptions that all ribosomes complete translation, and are not subject to regulated translational pausing or abortion at the time of capture or at any time prior to finishing translation. Additionally, the method itself may miss ribosomal footprints if nuclease digestion is incomplete, and give rise to false readouts of translation from contaminating non-coding RNA fragments. In contrast, assessing translation at the level of synthesized protein, e.g. through quantitative proteomics, should avoid errors associated with inferring protein synthesis rates from ribosomal occupancy, with the caveat that sensitivity limits relative to transcriptomic approaches may make transcriptomics the method of choice when starting material is low. We believe a potential major advantage of POPPi over existing methods for measuring cell type-specific protein synthesis is its efficiency, particularly for visualizing protein synthesis – PhAc-OPP labeling coupled to AF488azide conjugation can be completed within a few hours (see Methods). Future work will seek to understand the full capabilities and limitations of POPPi, e.g. for profiling rare cell populations in the brain.”How available are the reagents needed for POPPi, and are they easy to obtain by any research lab?PhAc-OPP is not currently commercially available, yet its chemical synthesis has been previously described in detail (Reference 12) which labs can use to have the compound synthesized, e.g. through a university chemistry core or a company. All other compounds used for the methods described are commercially available, including AF488-azide for visualizing protein synthesis and desthiobiotin-azide for enriching labeled protein. All reagent details are provided in the key resources table. PGA transgenic flies will be made available upon request, as indicated in the manuscript.The reagent AF488-azide is referred to differently in different places in the manuscript and was not well introduced or described.We now consistently refer to this reagent in its short form (AF488-azide) throughout the manuscript except when introducing the reagent in the Methods, where we added the statement “Detection of OP-puromycylated protein was achieved by conjugation to a fluorophore-azide called AF488 picolyl azide (AF488-azide) via CuAAC click reaction”. We regret the prior lack of clarity.Because OPP incorporation is sequence-independent, it should be able to label and terminate a peptide chain at any amino acid residue. Therefore I would expect the western blot to show a wider band or a smear after OPP or POPPi labeling. However, all the blots shown in the paper show similarly sharp bands as in the corresponding controls. Can the authors provide an explanation? Are the shorter (incomplete) peptides being degraded very quickly?It is likely that truncated proteins would be targeted for eventual degradation and depleted from the protein pool as the reviewer indicates. However, another simple explanation is that commercially available antibodies used for Brp, Synapsin and Draper are all reported to recognize epitopes at the C-terminal end of these proteins, which would be absent in most truncated protein and therefore not detectable on Western blot. The epitope for Syntaxin has not been mapped. Hence, the combined depletion of truncated proteins in addition to an inability to detect them using the available antibodies used in this study likely explain their absence of western blots. We added this interpretation to the Discussion (line 337).Reviewer #3 (Recommendations for the authors):1. It is not clear what percentage of the newly synthesized polypeptides incorporate puromycin which would allow visualization or immunopurification of the protein through the use of azide conjugates. Since the inclusion of puromycin in the nascent peptide prevents further elongation of the nascent peptide, reaching the levels of puromycin to saturate the cells would likely be detrimental. On the other hand, when lower amounts of puromycin are used, it is likely that the lower expressed genes/polypeptides will not be labelled. In any case, the authors should estimate the ratio of the newly synthesized targeted by puromycin. This can be done by using PhAc-OPP in elav-Gal4 UAS-PGA brains in combination with azide-biotin and S35 methionine. This would allow immunopurification with an antibody specific for a protein (such as bruchpilot), measuring the level of S35, and a second immunopurification with streptavidin and measuring again with S35. This can allow the estimation of the percentage of newly synthesized proteins that are targeted by PhAc-OPP.35S signal for any single protein-of-interest would have to be distinguished from all the other proteins in the eluate. This is potentially feasible by combining autoradiography with western blot, yet due to the antibody issue mentioned above, we would again likely miss any truncated labeled protein present.This is conceptually an interesting approach, although we believe there are major practical constraints that render this approach and the suggested experiment unlikely to provide quantitatively meaningful results. First, IP would likely not work well since the available antibodies to our assessed cell type-specific proteins bind to Cterminal epitopes, thus missing any truncated protein fragments and therefore likely a substantial portion of labeled newly-synthesized protein. Second, streptavidin enrichment is expected to enrich all labeled cellular protein, not just the protein-ofinterest, and hence, the 2. It is not clear how there can be clear full-size bands in the Western blots in figure 3. The addition of PhAc-OPP should truncate the protein at random sites that correspond to where the OPP is added to the nascent peptide. This should result in smears in principle unless there is a tendency of OPP to get incorporated towards the end of the protein. An explanation should be included in the discussion to help the reader understand the data better. This also undermines the argument that the fact that there are bands of different sizes suggests that the proteome is uniformly targeted. Since puromycin addition truncates the gene products at random positions, the band sizes should not be informative and indicative of unbiased labelling of the proteome.Please see response to the last comment of Reviewer 2.3. Although the imaging using OPP and Alexa488-azide looks rather uniform labeling in figure 1C when PhAc-OPP is used in combination with elav-Gal4 or repo-Gal4 UAS-PGA, the Alexa488-azide signal is much more salt and pepper distributed in figure 2A and D . This is especially prominent in glia where very few of the mCherry expressing cells are labelled by Alexa488-azide in Figure 2D. This suggests that the proteome of some cells will be much higher represented in the samples when azide-biotin is used to immunopurified proteins expressed by a cell type, severely limiting the use of the technique.To clarify, glial cell bodies populate the brain cell cortex at much lower numbers than neurons, but cortex glia form an extensive network around their surrounding neurons with each glial cell encapsulating many neurons. This gives the membrane-tethered mCherry signal a honeycomb-like appearance where the majority of mCherry signal is not from glial cell bodies but from glial membrane extensions that spread across the neuronal network . While these membrane extensions do not appear AF488-azide labeled, most of the solidly-filled glial cell bodies do, consistent with predominant cell body protein synthesis labeling we observe with neurons and with unblocked OPP. However, we acknowledge that there appears to be more overall cellto-cell variability in generally cellular AF488-azide signal when brains are incubated in PhAc-OPP compared to unblocked OPP, although there is also some variability in labeling with unblocked OPP , which is not dependent on PGA-induced unblocking. This suggests that variability in protein synthesis labeling may be partly due to cell-to-cell differences in global translation, and partly due to differences in PGA expression (see below).4. The fact that OPP-mediated labeling is quite uniform suggests that the translation levels do not change very much between cells and the reason for the non-uniform signal in figure2 may result from the non-uniform expression of UAS-PGA. The authors should stain the elav-Gal4 or repo-Gal4 UAS-PGA with an anti-Flag antibody to check for non-uniform expression of PGA.elav-Gal4>UAS-PGA adult brains and observed non-uniform FLAG levels between cells suggesting a degree of cell-to-cell variability in PGA expression. The data are presented in Figure 2 —figure supplement 1 and described in the Results (line 168).We performed FLAG immunostaining of 5. In figure 1 figure supplement 2B the authors should test incubation times that are between 0-2 hours better since at 2 hours the system already seems to be saturated.Indeed, at 2h of labeling with unblocked OPP labeling, AF488-azide signal is close to maximal and based on this OPP result, we focused on shorter time points (e.g. 1 hour) with PhAc-OPP . We did not pursue additional time points with unblocked OPP, since PhAc-OPP is the main focus of our study.Reviewer #1 (Recommendations for the authors):The authors satisfied the major concerns in my original review. However, I have an additional major concern.The data presented do not convince me that POPPi is a robust and useful method for capturing and identifying newly-synthesized proteins in a cell type-specific manner (e.g. w/ biotin-azide). In the response to my concern of my original review, the authors suggest that background bands seen in negative control lanes of western blots  are due to non-specific AF488-azide incorporation into all proteins (newly synthesized + old). This is unexpected to me, as I had assumed the click chemistry was specific to OPP-labeled proteins. Regardless, assuming that non-OPP-labeled proteins are labeled by AF488-azide, I interpret the western blots in Figure 4A and Figure 4C as showing weak 'signal above background'. This is especially concerning because Figure 4A,C were performed by labeling a large portion of the cells within the collected tissue (pan-neuron and pan-glia). So, labeling in smaller subsets of cell types (e.g. dopaminergic neurons) would be expected to result in even lower 'signal above background'. I outline below additional thoughts and suggestions that could help address my concerns.We are pleased that our resubmitted manuscript satisfied major concerns in the Reviewer’s original review.Regarding the additional point raised, it is important to note that the presence of background AF488-azide binding to protein is mainly restricted to brain lysates as we do not see significant background in control groups assessed in confocal imaged wholemount brains  or other fly tissues  incubated in PhAcOPP then in AF488-azide. We would also like to point out that these gels show total brain lysates, i.e. there is no enrichment for labeled protein. As indicated in our original response, our primary intended application for the AF488-azide reagent is to visualize protein synthesis by confocal imaging whole-mount brains . The data in previous Figures 4A and 4C were only intended to show that protein synthesis visualized in brains imaged by confocal microscopy was not merely derived from just a few labeled proteins, but from a range of proteins that span the molecular weight range of the gel.In order to address the Reviewer’s concern, we have performed additional experiments to incorporate the requested control group for in-gel fluorescence assays and also to show total OPP-labeled protein from neuronal and glial proteomes by the biotin tagging and pulldown method, as described more below. Our new data clearly demonstrates strong signal-to-background for cell type-specific protein synthesis labeling by PhAcOPP, that matches the strong signal-to-background already seen in imaging data from fly brain and other tissues. This, coupled to data showing our ability to enrich for cell type-specific proteins following labeling in targeted cell populations provides rigorous quality control for our method and demonstrates its clear utility for achieving robust cell type-specific protein synthesis labeling.Recommendations for the authors:1. To more accurately assess the signal-to-background of cell type-specific labeled proteins, the authors should provide a proper negative control in Figure 4A and 4C. The "vehicle-only" negative control may underestimate the background levels of AF488-azide incorporation. I would argue that the most appropriate negative control is to incubate wild-type brains (e.g. elav>GFP) with PhAc-OPP. Hypothetically, PhAc-OPP could be uncaged by endogenous fly enzymes, which would result in higher background levels than the vehicle-only control. As far as I can tell, the possibility of uncaging PhAc-OPP without PGA is not discussed and remains untested in this manuscript. Furthermore, line 203 "PGA-dependent unblocking of PhAc-OPP…" is thus not supported by their data using the "vehicle-only" negative control in Figure 4. I suggest that the authors repeat the data in Figure 4A and 4C using the appropriate negative control I mentioned.The negative control indicated by the Reviewer was included in the manuscript, not for the data in Figure 4, but for confocal imaging of protein synthesis in whole-mount brains. Specifically, we showed the absence of protein synthesis labeling when brains are incubated with PhAc-OPP but the PGA transgene is not expressed . Hence, we had previously addressed the possibility of PGA-independent PhAc-OPP uncaging and shown via the control group in Figure 2—figure supplement 1b that there is no substantial uncaging of PhAc-OPP without PGA expression.However, to fully address any potential concerns of the Reviewer, we repeated the in-gel fluorescence assay incorporating the additional control group requested with brains incubated in PhAc-OPP but not expressing PGA . For this control group, we chose flies that harbor the UAS-PGA transgene but no GAL4 driver, hence they are unable to express PGA. Exactly as seen with confocal brain imaging, this control group does not show any substantive protein synthesis labeling visualized by A488-azide signal , again consistent with a lack of PhAc-OPP uncaging in the absence of PGA expression. We have added this new data as new Figure 4A and also added text to the Results (line 164) in order to describe this control group more clearly in the manuscript.Drosophila contains naturally biotinylated proteins, these new western blots would provide the fairest representation of signal-to-background. For example, naturally biotinylated proteins will bind to the streptavidin beads and thus be background on western blots and in Mass spectrometry (MS) data.2. The authors should provide western blots similar to Figures 4A,C, but using the biotin-azide labeling reagent. Since biotin-azide enables researchers to capture and detect OPP-labeled proteins using streptavidin-bead pulldown, it is critical that researchers understand the global signal-to-background when using this reagent. I suggest that the authors repeat Figure 4A,C using biotin-azide to label and streptavidin-fluorophore to detect. Furthermore, since We performed the experiments requested in order to observe total biotin-tagged protein signal from neurons or glia following pulldown with neutravidin beads. The approach described by the reviewer (biotin-azide capture of OPP-labeled protein followed by pulldown with avidin beads) is the same approach we had used in blots to detect enrichment of individual neuron-specific or glial-specific proteins , hence we used these samples to blot for global biotin-tagged protein as requested by the Reviewer. We used anti-biotin to do this instead of streptavidinfluorophore suggested by the Reviewer, as anti-biotin is well validated for western blots on fly tissue (Reference (12)). Using this approach, we observe strong biotin-tagged protein signal in eluted fractions from PhAc-OPP-treated brains and very little background in the vehicle-treated control group likely corresponding to endogenously biotinylated proteins present in flies . Biotin-tagged protein can also be seen in inputs (whole lysates) for PhAc-OPP-treated brains and this is weaker than in eluted fractions, as would be expected. As the reviewer indicates, naturally biotinylated proteins are present in flies and can manifest as background on western blots. Consistent with this, we find one major non-specific band across all groups and present in both input and eluates. Hence, these new data demonstrate very high signalto-background for enriched biotin-tagged proteins. We believe these data address the concern about signal strength in in-gel fluorescence assays as pulldown of biotin tagged protein is a preferred method for assessing global labeling signal, as indicated by the Reviewer.3. I would like to see MS data to support the data presented in Figure 4 B,D. These figures show that POPPi can enrich cell type-specific labeled proteins. However, the background bands for Synapsin, Syntaxin, and Draper are concerning and suggest the sensitivity of this method is low. To convince me that there is global signal over background, I would like to see MS analysis of samples in Figure 4B,D. For example, MS of streptavidin-pulldown from the following brain genotypes (1) elav>PGA + PhAc-OPP, (2) repo>PGA + PhAc-OPP, (3) elav>GFP + PhAc-OPP. Using quantitative approaches such as TMT labeling or SAINT analysis, I would expect to see enrichment of Draper to glia and Syntaxin to neurons, for example.Considering our new data from analysis of total biotin-tagged neuronal/glial protein  alongside confocal imaging data from brains  and imaging data from other fly tissues such as muscle, trachea, salivary glands, fat body , we have now demonstrated that our method achieves robust signal over background for labeling newly-synthesized protein using two independent approaches. We have also shown that our method can be used to enrich cell typespecific labeled proteins from neurons and glia , thus verifying its use for assessing nascent proteomes of targeted cell populations. There are minor background bands for some  enriched proteins, but these individual protein blots only detect near full-length labeled protein, whereas the total biotin blots should be able to detect all labeled protein or protein fragments and show a much greater signal-to-background strength . In future studies, we plan to use MS to query cell type-specific proteome changes under altered physiological or pathological conditions, yet it will require significant time, effort and funds to optimize and carry out MS studies. We believe that through the rigorous quality control experiments already performed, we have been able to effectively demonstrate high signal to background using two separate approaches, and therefore MS is not necessary for this purpose.Reviewer #2 (Recommendations for the authors):I'm generally satisfied with the responses and changes to the manuscript. My only remaining request is that the authors include a line for PhAc-OPP in the Key Resources Table. Clearly, this is a key reagent, and the authors should be transparent that it is something that needs to be synthesized, which will likely limit how widespread the method is used by the community.We are pleased that the changes made are satisfactory to the Reviewer. We have added PhAc-OPP to the Key Resources Table and cited the article in which its chemical synthesis is described in detail.


Humanness is an important characteristic for facilitating interpersonal communication, particularly through avatars in the metaverse. In this study, we explored the mirror neuron system (MNS) as a potential neural basis for perceiving humanness in avatars. Although previous research suggests that the MNS may be influenced by human-like shape and motion, the results have been inconsistent due to the diversity and complexity of the MNS investigation. Therefore, this study aims to investigate the effects of shape and motion humanness in avatars on MNS activity. Participants viewed videos of avatars with four different shapes  and two types of motion (HumanMotion and LinearMotion), and their μ-wave attenuation in the electroencephalogram was evaluated. Results from a questionnaire indicated that HumanMotion was perceived as human-like, while AbbreviatedShape and ScatteredShape were seen as non-human-like. AngularShape’s humanity was indefinite. The MNS was activated as expected for avatars with human-like shapes and/or motions. However, for non-human-like motions, there were differences in activity trends depending on the avatar shape. Specifically, avatars with HumanShape and ScatteredShape in LinearMotion activated the MNS, but the MNS was indifferent to AngularShape and AbbreviatedShape. These findings suggest that when avatars make non-human-like motions, the MNS is activated not only for human-like appearance but also for the scattered and exaggerated appearance of the human body in the avatar shape. These findings could enhance inter-avatar communication by considering brain activity. While cMNS has been reported to respond to avatars with human-like shapes. Regarding the perception of the shape of an agent as a communication target, previous studies have compared human-shaped with non-human-shaped stimuli, such as animals or non-living objects. Specifically, it has been reported that ventral cortical visual tracts associated with the MNS were activated for human shapes while using extreme differences in depiction as the stimulus condition . In the Additionally, it was reported that both the human-like shape of the avatar and its human-like motions are related to the activation of the MNS. Previous studies have compared the effects of motion observations performed by humans and robots and found an involvement of sensorimotor brain regions associated with the MNS, collectively referred to as the action observation network (AON) which facilitated motion responses more when the agent was human than when it was not . For exaOn the other hand, MNSs were also reported to be more broadly sensitive to avatar motions compared to avatar shapes. Previous studies on MNS activation in response to human motion suggested that the superior temporal sulcus associated with the MNS responds to human motion even in the absence of an explicit human shape . Cross eBased on these prior reports, it is possible that avatar shape characteristics may alter MNS sensitivity when the avatar’s motions are not human-like. Exaggerated representation of body parts associated with humanity in avatar shape has the potential to be sensitive to MNS activation even if the avatar performs non-human-like motion. However, MNS activities for avatars in the virtual world, which have a high degree of freedom of shape and motion, have not been fully investigated or clarified, and this is a remaining problem. Specifically, avatars in a virtual environment can be configured to look and move even more freely than robots. Therefore, there is a need to investigate virtual avatars that resemble humans separately from robots. In addition, there has been no systematic investigation of the effect of the combination of shape and motion humanness on MNS activity from the viewpoint of EEG μ-wave attenuation.Therefore, the purpose of this study was to investigate the effects of virtual avatars’ shape and motion humanness on MNS activity. This study measured and compared EEG μ-wave attenuation as a measure of MNS activity when observing avatars with human and nonhuman shapes and motions. This study used a combination of four avatar shape conditions and two avatar motion conditions to investigate whether there is a difference in MNS activation when participants observe two different motion patterns for each of the four different shapes of the avatar. The two different motion patterns of the avatar consisted of the HumanMotion and LinearMotion conditions for the human- and non-human-like motion patterns, respectively. 2.2.1.Twenty-two healthy right-handed participants  between the ages of 21 and 29  were tested. Data from 16 participants  were ultimately used in the analysis [21–29 years old ]. All experimental subjects were confirmed to be neurotypical. Data from four participants were excluded from the analysis due to measurement problems (excessive eye blink artifacts) and from two participants who had problems performing the task. Participants were first briefed on precautions related to the experiment and signed a consent form. The study was approved by the Ethical Review Committee for Research Involving Human Subjects at the Tokyo Institute of Technology.2.2.The experimental setup is illustrated in 2.3.A Dell Latitude 3,301  was used as the video-PC, and a dedicated MATLAB  script was created for video playback and trigger transmission. The videos were played on a 24-inch monitor . A 32-channel electroencephalograph actiCHamp  was used for EEG measurements. The measured EEG was played back on the measurement-PC  using Brain Vision Recorder (Brain Products GmbH). To record the trigger signals sent from MATLAB, a trigger box  was used to connect the EEG to the video-PC.2.4.Avatar shape and motion conditions were combined for the videos. There were four avatar shape conditions  and two avatar motion conditions (HumanMotion and LinearMotion). Therefore, eight different videos were created for the conditions in which the avatars would appear: HumanShape & HumanMotion, HumanShape & LinearMotion, AngularShape & HumanMotion, AngularShape & LinearMotion, AbbreviatedShape & HumanMotion, AbbreviatedShape & LinearMotion, ScatteredShape & HumanMotion, and ScatteredShape & LinearMotion.In the avatar motion conditions, as shown in To create a video of an avatar performing a human-like ball grasping motion for the HumanMotion condition, the study first recorded a person grasping and lifting a desk ball before placing it back on the desk using a video camera. The video was then analyzed frame-by-frame, with the position of each joint in the person’s body recorded for each frame. Using this data, this study determined the position of each joint in the avatar’s body for each frame in its video. Motion tracing techniques were then employed to generate a video of the avatar performing the same motion as the person, resulting in a realistic simulation of the ball’s grasping motion.In the LinearMotion condition, non-human, linear, and constant velocity animations were created based on previous research  by traciIn the avatar shape conditions, as shown in In addition, videos for the control and baseline conditions were created. For the control condition, a video with a hidden avatar was created that only showed the ball movement. In this video, the MNS was expected to be inactive because no humanness information was present in shape and motion. Videos for the baseline condition, which were needed for the EEG analysis, were created using white noise. Several Gaussian noise images with a standard deviation of 100 were generated on Google Colaboratory . The frame rate for all videos was 30 fps, and the length was approximately 2.5 s.In summary, the participants in the experiment watched a total of 10 types of videos: four conditions for avatar shape times two conditions for the motion assigned to each avatar plus videos from the control and baseline conditions.The ten videos for each experimental condition used in the study can be viewed in the 2.5.As shown in The videos were presented on the playback monitor with a height of approximately 8 cm and a width of 13.3 cm. To block external sounds, white noise was played through the earphones while the videos were being played. Immediately before the start of the video playback, the participants were instructed to observe the video carefully and to avoid body movements and blinking of the eyes as much as possible.As shown in As shown in 2.6.During the experiment, participants wore dedicated 32-channel electrode caps  on their heads. Measurements were taken at a sampling rate of 500 Hz, while the impedance between each electrode and the scalp was kept below 10 kΩ by applying a dedicated gel . Fz was used as the reference electrode for EEG recording. The ground electrode was placed on the forehead (near FPz).2.7.EEGLAB , a MATLAB toolbox, was used to analyze the EEG data. After removing power line noise from the data of each electrode, a bandpass filter from 0.1 to 30 Hz was applied, and the data were re-referenced to TP9 and TP10 as both mastoids. Each experimental condition’s video was presented in a randomized order for every block, as illustrated in t-test was performed on the log ratios of the μ-waves in each condition to determine whether they were significantly negative and different from zero. Electrodes covering the central sulcus areas on either side of the sulcus (C3 and C4), which are considered to reflect the activity of the MNS, were the target of the analysis.The average power of the μ-waves in each condition was divided by the average power of the μ-waves in the baseline condition, and the log-transformed value was used as the amount of change in the μ-waves for the evaluation. By using the ratio to the baseline condition, comparisons can be made between conditions, while minimizing the effect of interindividual differences. A negative log ratio means that the μ-waves were significantly reduced compared to the baseline condition, indicating μ-wave attenuation and suggesting MNS activation. Student’s 2.8.The avatar shape was subjectively evaluated by displaying one still image of each avatar on a video playback monitor. Participants responded orally to a set of questions about the humanness of the avatar shape, which were based on components from the uncanny valley study . The que3.p < 0.05 for both C3 and C4 channels in all conditions). Student’s t-test was performed to determine whether the μ-wave attenuation in each condition was significant, meaning that the log ratio was significantly negative. In the control condition, the μ-waves were not significantly attenuated in either the C3 or C4 channels. In the HumanMotion condition, significant μ-wave attenuation was observed in both the C3 and C4 channels, regardless of the avatar shape. On the other hand, the LinearMotion condition, in which non-biological motion was applied, showed different trends among conditions. Significant μ-wave attenuation was observed in both the C3 and C4 channels for the HumanShape and ScatteredShape conditions, whereas it was only observed in the C3 channel for the AngularShape and AbbreviatedShape conditions.The experimental conditions were compared based on the results of μ-wave attenuation in the C3 and C4 channels of the EEG which are shown in Additionally, this study required participants to observe a video about the avatars. Therefore, a secondary task was conducted to ascertain whether or not participants had observed them. In the secondary task, the video was stopped multiple times at random, and participants were asked to silently count the number of stops without using their fingers and to respond verbally after the video ended. Participants who answered less than 50% of the tasks correctly were considered to have failed to pay sufficient attention to the experiment being conducted and were excluded from the data analysis. As a supplementary result, the average percentage of correct responses to the secondary task was 90.28% (SD = 6.94%). The total number of incorrect responses for the 16 participants in each condition is listed in p-values for each avatar shape condition: HumanShape , AbbreviatedShape , ScatteredShape , and AngularShape . These findings suggest that the HumanShape condition provided human-like avatar shape information to the experimental participants, whereas the AbbreviatedShape and the ScatteredShape conditions provided non-human-like avatar shape information.The study utilized a questionnaire to subjectively evaluate the humanness of the avatar using three indices from the uncanny valley study : humanli4.Using the scales of humanness , the subThis second discussion is with respect to the results of EEG analysis for each avatar experimental condition as objective evaluation. In this study, μ-wave attenuation at electrodes covering the central sulcus areas on either side of the sulcus (C3 and C4), which reflect activity in the MNS, was used as an objective evaluation index of brain activity. For each experimental condition, the value of the log ratio of the EEG power between the μ-wave band and baseline condition was analyzed to determine whether significant μ-wave attenuation was present. First, no significant μ-wave attenuation was observed in the control condition, in which only a ball motion was presented. This result replicated previous studies .In the HumanMotion condition with biological motion, significant μ-wave attenuation was observed in channels C3 and C4 in all four avatar appearance conditions, which means that brain activity based on changes in avatar shape suggested similar trends. On the other hand, in the LinearMotion condition, in which non-biological motion was added, there were differences in activity trends depending on the avatar shape. Significant μ-wave attenuation was observed in channels C3 and C4 for the HumanShape and ScatteredShape conditions. In contrast, the AngularShape and AbbreviatedShape conditions only showed significant μ-wave attenuation in C3 but not in C4.The HumanShape condition showed relatively human-like shapes compared to the AbbreviatedShape and ScatteredShape conditions. In the HumanMotion condition, the MNS was activated when the participants observed avatars consisting of a combination of the HumanMotion condition and any avatar shape conditions, meaning that the observation of human-like motion was associated with MNS activity. On the other hand, in the LinearMotion condition, MNS activation varied according to the avatar shape conditions.The AbbreviatedShape and ScatteredShape conditions, which appeared relatively less human-like, also showed different results. This is a novel piece of evidence that demonstrates that even if humans do not consciously perceive the avatar as human-like, they can still perceive it to be human-like.In interpreting the experimental results of this study, it is important to note that a previous study by In the HumanShape condition, μ-wave attenuation was observed in the C3 and C4 channels in both HumanMotion and LinearMotion conditions. Thus, activation of the MNS was observed for human-like avatars. Similarly, in previous studies, the ventral cortical visual pathways associated with the MNS were activated in response to human-like depictions, compared to non-human stimuli such as animals or non-living things .In the HumanMotion condition, μ-wave attenuation was observed in both C3 and C4 for all shapes: HumanShape, AbbreviatedShape, and ScatteredShape. Thus, activation of the MNS was observed for avatar motion humanness. Similarly, in previous studies, the superior temporal sulcus associated with the MNS responded to human-like actions, even in the absence of a clear human form . When thWith respect to avatar motion without humanness, the results varied with avatar shape conditions. For the ScatteredShape with the LinearMotion condition, μ-wave attenuation was observed in both C3 and C4, indicating activation of the MNS. In contrast, for the AbbreviatedShape condition with the LinearMotion, μ-wave attenuation was observed only in C3 but not in C4, indicating non-activation of the MNS. Thus, in the LinearMotion condition, when the avatar shape was varied and human-like and non-human-like motions were performed, the MNS showed different activation patterns for each condition. This indicated that it is important to take their characteristics into account to facilitate communication by using avatars.In the ScatteredShape condition, MNS activation was observed for both the HumanMotion and LinearMotion conditions. The avatar in the ScatteredShape condition was not human-like. In other words, in avatars that were non-human-like, the MNS was activated when non-human-like motions were performed.Similar results have been reported in previous studies. When participants saw actions performed by humans or a robot, no differences in brain responses were observed . The lefIn the AbbreviatedShape condition, MNS activation was observed in the HumanMotion, but not in the LinearMotion condition. The MNS was not activated when the avatar, which was non-human-like in appearance, performed non-human-like actions.In previous studies, the MNS associated with the right premotor cortex was more involved during the observation of reaching movements performed by human hands compared to robot crimpers . Thus, oAs a result of the current research, even if the avatar shapes of the AbbreviatedShape and the ScatteredShape condition were perceived as non-human-like, the MNS responded to the ScatteredShape in the LinearMotion condition, but not to the AbbreviatedShape condition. This suggests that there is a condition for the shape to which the MNS is sensitive when we consider an avatar with a less human-like shape. The main difference between the AbbreviatedShape and the ScatteredShape condition was whether the avatar’s body parts were drawn continuously or discontinuously. Therefore, when an avatar’s movements are not human-like, the MNS may perceive the continuous nature of the shape as dehumanizing. It has been suggested that if the avatar’s movements were not human-like, the MNS would be sensitive to the discontinuity of the avatar’s shape. In this study, the videos used in each experimental condition did not depict the avatar’s face, which prevented any MNS effects related to facial depiction. Previous research by An interesting experimental result of this study is that the exaggerated shape of the avatar’s arms may have affected the activation of the MNS when the avatar’s movements were not human-like. Indeed, such results were obtained under the experimental conditions of the ScatteredShape avatar. This may suggest that exaggerated human functional body parts may be specifically related to the perception of humanness. This study used EEG measurements to detect MNS activation. However, recent studies have attempted to use more detailed observation of brain activity, such as fMRI . The comThe limitations of this study are as follows. The experiments were conducted with four avatar shape conditions and two avatar motion conditions. Further details would require setting up additional experimental conditions and conducting additional experiments. Appearances such as the color of all avatars in this study were similar. However, there is a variety of appearances when actual communication is assumed. Therefore, further investigations of the effects of varied avatar appearances are required. EEG μ-wave attenuation was used as an objective evaluation index. However, previous studies have pointed out that mu attenuation may be disrupted by changes in attention because the mu frequency band overlaps with the alpha frequency band, which is sensitive to changes in attention . In addiIn the AngularShape condition, subjective evaluation using a questionnaire did not provide a clear distinction between whether the avatar of the AngularShape condition was perceived as human-like or non-human-like. Therefore, the finer condition differences included in the AngularShape condition were not considered. Investigating the details of humanness is a topic that requires further exploration in future studies.This study builds upon previous research by This study designed an experiment based on the previous study by In this study, to record baseline activity, a separate baseline condition was used consisting of white noise. On the other hand, in previous reports , the supThe main manipulation in this study involved the presence/absence of human-like motion and shape in the avatar. However, it is known that the observation of goal-directed actions activates the MNS regardless of the specific motion and shape of the avatar . The tasTo date, no previous studies have investigated the EEG-based MNS while simultaneously manipulating both human-like appearance and movement. To the best of our knowledge, this is the first experimental investigation to explore this perspective, providing initial insight into the characteristics of EEG-based MNS when simultaneously altering human-like appearance and movement. Furthermore, this study addresses the issue of inconsistency in previous research regarding the combination of human form and movement, which has been suggested to influence MNS activity. However, while this study contributes to our understanding of MNS activation, the results did not fully confirm the consistency of previous research, and further investigation is necessary to fully elucidate the complex relationship between appearance and movement in the context of MNS activity.Regarding the analyzed regions of this experiment, in addition to the parietal cortex, the premotor cortex  has been reported to be involved in the processing of action goals and kinematics during the observation of robots and human agents . However5.This study aimed to explore the influence of avatar shape and motion humanness on MNS activity using EEG μ-wave attenuation. Four avatar shapes were used  and two motions were examined (HumanMotion and LinearMotion). Results from a questionnaire revealed that HumanMotion was perceived as human-like, while AbbreviatedShape and ScatteredShape were seen as non-human-like. Here, AngularShape’s humanity was indefinite. As expected, the MNS was activated for avatars with human-like shapes and/or motion. However, for non-human-like motion, there were differences in activity trends depending on the avatar shape. Specifically, avatars with HumanShape and ScatteredShape in LinearMotion activated the MNS, while the MNS was indifferent to avatars with AngularShape and AbbreviatedShape in LinearMotion. Comparing the ScatteredShape condition avatar with the AbbreviatedShape condition, the ScatteredShape condition avatar placed a greater emphasis on the functional part of the hand. The position of the hand was clearly visible, indicating that the MNS may be particularly sensitive to functional body parts, such as a hand grasping a ball, even when the deformed human-shaped avatar looks less human-like and has robot-like movements. These findings suggest that when avatars make non-human-like motions, the MNS is activated not only for human-like appearance but also for the scattered and exaggerated appearance of the human body in the avatar shape. Overall, this study contributes to research on inter-avatar communication, considering brain activity and the MNS, and has the potential to facilitate interpersonal interactions in cyberspace, including the metaverse with highly flexible avatars.The raw data supporting the conclusions of this article will be made available by the authors, without undue reservation.The studies involving humans were approved by the Ethical Review Committee for Research Involving Human Subjects at the Tokyo Institute of Technology. The studies were conducted in accordance with the local legislation and institutional requirements. The participants provided their written informed consent to participate in this study.YuM, HU, and YoM contributed to the conception and design of the study, developed and implemented the system, conducted the evaluation experiment, discussed and interpreted the results, drafted the manuscript, and reviewed the manuscript. All authors contributed to the article and approved the submitted version.


Accumulating evidence supports that physical exercise (EX) is the most effective non-pharmacological strategy to improve brain health. EX prevents cognitive decline associated with age and decreases the risk of developing neurodegenerative diseases and psychiatric disorders. These positive effects of EX can be attributed to an increase in neurogenesis and neuroplastic processes, leading to learning and memory improvement. At the molecular level, there is a solid consensus to involve the neurotrophin brain-derived neurotrophic factor (BDNF) as the crucial molecule for positive EX effects on the brain. However, even though EX incontestably leads to beneficial processes through BDNF expression, cellular sources and molecular mechanisms underlying EX-induced cerebral BDNF overproduction are still being elucidated. In this context, the present review offers a summary of the different molecular mechanisms involved in brain’s response to EX, with a specific focus on BDNF. It aims to provide a cohesive overview of the three main mechanisms leading to EX-induced brain BDNF production: the neuronal-dependent overexpression, the elevation of cerebral blood flow (hemodynamic hypothesis), and the exerkine signaling emanating from peripheral tissues . By shedding light on these intricate pathways, this review seeks to contribute to the ongoing elucidation of the relationship between EX and cerebral BDNF expression, offering valuable insights into the potential therapeutic implications for brain health enhancement. Being physically active reduces not only the risk of developing cardiovascular, metabolic and chronic diseases but also brain disorders. Indeed, numerous studies reported the beneficial effects of EX across a lifespan on cognitive functions and neuroplastic mechanisms . EX redubdnf gene corresponding to a valine-to-methionine substitution), which is associated with a defect in activity-dependent regulated secretion, attenuates the cognitive advantage of EX  and the regulation of synaptic plasticity . It has ge of EX . The synIn this context, this review aims to provide a comprehensive overview of scientific evidence on the different molecular mechanisms explaining how EX leads to cerebral BDNF upregulation. It is important to underscore that within the context of this review, the term “EX” has been utilized inclusively, encompassing a wide range of physical activities, irrespective of their specific type, duration, or intensity while these factors influence the cerebral expression of BDNF . After a2.2.1.in vivo removal of cerebral endothelium using a detergent (3-[(3-cholamidopropyl) dimethylammonio]-1-propane sulphonate, CHAPS), halved the cerebral BDNF content . Each 5′ non-coding exon is spliced into the coding exon that encodes a similar BDNF protein product  or extracellularly  in mature BDNF . Of notenditions . BDNF isnditions . Accordi product . Thus, t product . Concern product . Besidesse to EX .2.3.NTR), the affinity being much higher for TrkB than p75NTR  receptor and pan75 neurotrophin receptor  at the cell membrane, triggering the influx of extracellular Ca2+ into the cell. In terms of ligand-gated channels responsible for Ca2+ entry into neurons after EX, different mechanisms have been proposed involving preponderantly glutamatergic transmission through α-amino-3-hydroxy-5-methyl-4-isoxazolepropionic acid (AMPA) and N-methyl-d-aspartate-type (NMDA) receptors  able to drive activity-dependent induction of promoter IV. Among the three DNA sequences that are cooperatively recruited for Ca2+-induced bdnf promoter IV expression, 2+-response factor (CaRF) is a regulator of activity-dependent bdnf gene expression through CaRE1 and that the transcriptional activity of CaRF is dependent on Ca2+ influx in a neuron selective manner. CaRE3 has also received specific attention. Indeed, once bounds by CREB (cAMP response element-binding protein), this latter is phosphorylated on serine 133   , Ras/MAPe (CAMK)  and the e (CAMK)  systems.e (CAMK) , EX-indu3.2.bdnf gene expression  pathway, cleaved from fibronectin type III domain-containing protein 5 (FNDC5) and released in blood circulation . In addi pathway .3.4.bdnf gene transcription associated with cognitive improvement. For example, the research conducted by bdnf transcription , histone acetylation  or deacetylation . Thus, various studies have demonstrated that different models of EX lead to the modulation of HAT, DNMT, and HDAC activities at BDNF promoters . These ccription . Additioovements . Using paragraph . On the aragraph . Other maragraph  and it haragraph . However3.5.bdnf gene expression as stated in a precedent section. This notion is supported by the findings of Ding, Ying, and EX is known to increase CBF in sensorimotor region and areas involved in cognitive capacities such as the prefrontal cortex, hippocampus and amygdala . ConsideStrong evidence in favor of the hemodynamic hypothesis is also provided when strategies to reduce CBF were applied. One-week daily EX in rats with unilateral carotid occlusion (irreversible clamping) did not increase cortical BDNF levels in ipsilateral compared to exercised rats without carotid occlusion . MechaniNTR -dependent endocytosis which is subsequently re-secreted by astrocytes in its mature form  serve as fuel substrates that are upregulated in metabolic changes such as caloric restriction  or short hairpin RNA strategy, increases bdnf transcript expression  is a polypeptide hormone primarily identified in the liver, which can be transported to other tissues and act as an important mediator of body growth and tissue remodelling . Althoug4.1.3.Using liver specific Fibroblast growth factor 21 (FGF21) knockout mice, 4.1.4.Recently, using an elegant plasma transfer strategy, 4.2.Over an extended period, the term “exercise factor” served to depict molecules originating from contracting muscles, potentially orchestrating metabolic and physiological effects on central or peripheral organs. Among these factors, cytokines were the first reported in the literature  and it w4.2.1.bdnf gene expression was completely abolished. Conversely, intraperitoneal administration of lactate in mice elicited a hippocampal BDNF increase similar to that obtained in trained mice. The authors also reported that the improvement in learning/memory performance was dependent on BDNF as co-administration of lactate and a TrkB antagonist (CEP701) prevented this effect. Although the interaction between lactate and cerebral BDNF levels is not fully elucidated, some mechanisms have been proposed [For review  in neuronal cultures of mouse neocortex by potentiating neuronal NMDA glutamatergic transmission  binding on neurogliovascular unit   and partr review ]. Firstlsmission . Secondlsmission . Conversg/memory .4.2.2.4.2.2.1.fndc5 gene is not conserved from rodent to human resulting in very low translation efficiency  to kynurenic acid (KYNA). Indeed, tryptophan, primarily derived from the liver, is metabolized to KYN through indolamine-2,3-dioxygenase (IDO) . Interes animals . Consist animals . Collect4.2.3.Cathepsin-B (CTSB), a lysosomal cysteine protease ubiquitously expressed was identified in 2016 as a myokine by 4.2.4.BDNF is produced in skeletal muscle by various cell types, including myofibers, satellite cells, motoneurons and endothelial cells . BDNF hain vivo studies are needed to provide more conclusive evidence in support of this hypothesis.To address this question, particular attention should be provided to extracellular vesicles, especially exosomes. Based on the provided references, BDNF can be transported within exosomes,  and it h5.As the most downstream factor mediating EX-induced brain health, manipulating BDNF content in the brain has emerged as a promising strategy for mitigating cognitive deficits, addressing neurodegenerative disorders, counteracting age-related cognitive impairment, and promoting overall brain health. EX has been identified as a potent and robust non-pharmacological intervention for enhancing cognitive function and limiting cognitive deficits through increased brain BDNF levels. Recent research has shed light on two additional pathways, namely hemodynamic and humoral, which complement the well-established role of neuronal activity in modulating brain BDNF levels. Notably, these pathways offer more feasible and achievable pharmacological strategies for intensifying brain BDNF expression compared to the neuronal activity pathway, as they circumvent the challenges of drug delivery across the BBB and potential drug-related side effects on neurotransmission.However, the question of the relative contribution of each of these mechanisms to the beneficial effects of EX-induced brain BDNF increase remains complex and challenging to answer definitively. It is hypothesized that each pathway plays an essential role, as strategies that dampen any of these mechanisms individually have been shown to result in defective BDNF expression associated with cognitive impairment. It is plausible that these distinct mechanisms exist to offer a differential and persistent age-dependent temporal response, or to compensate for the deficiencies of one pathway with the others. Moreover, evidence suggests that these mechanisms are intricately interconnected, as neuronal activation is coupled with CBF regulation, and irisin, one of the well-studied humoral factors, has been found to modulate both vasorelaxation and neuronal activity. To understand the contributive part of the different pathways involved, employing transgenic mice with selective endothelial deletion of tPA or BDNF could provide valuable insights into the neuroplastic consequences of the hemodynamic pathway. Similarly, conducting studies that compare NMES to conventional models of EX would enable the isolation of the humoral muscle-brain crosstalk from the broader whole-body response. Indeed, this strategy would overcome an experimental bias as current studies investigating the muscle-brain dialogue are conducted following conventional protocols which engender a pre-dialogue between peripheral tissues that are also responsive to EX. The conversion of KYN into KYNA or the production of irisin by adipose tissue are some examples.In conclusion, manipulating brain BDNF content through non-pharmacological interventions such as EX has emerged as a promising strategy to enhance cognitive function and mitigate cognitive deficits. Recent findings on hemodynamic and humoral pathways provide additional insights into the mechanisms through which EX induces brain BDNF overproduction. Further research is warranted to better understand the contribution of each pathway to the beneficial effects of EX on brain health and cognitive function. In addition, due to a wide range of EX types and the complexity of their classification, it is crucial to keep in mind that the contribution of the pathways described could be contingent upon EX type , duration, intensity, frequency. Although this aspect has not been addressed in the manuscript, we encourage readers to consider this remark. Altogether, the findings on hemodynamic and humoral pathways will undoubtedly have implications for clinicians aiming to promote EX interventions or for scientists seeking to develop alternative strategies to mimic EX effects, particularly in populations who may face challenges with regular EX adherence. By unraveling the intricate interplay of these mechanisms, the scientific community can unlock the full potential of brain BDNF modulation for cognitive health and neuroprotection in various clinical and research settings.MC: Writing – original draft, Writing – review & editing. RC: Writing – original draft, Writing – review & editing. JW: Writing – review & editing. AM: Writing – review & editing. AQ: Writing – review & editing. CL: Writing – review & editing. AP-T: Writing – original draft, Writing – review & editing. PG: Writing – original draft, Writing – review & editing.