Antimicrobial peptides do not directly contribute to aging in Drosophila , but improve lifespan by preventing dysbiosis

  1. M.A. Hanson
  2. B. Lemaitre

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Abstract

Antimicrobial peptides (AMPs) are innate immune effectors first studied for their role in host defense against bacterial and fungal infections. Recent studies have implicated these peptides in the clearance of aberrant cells and various neurological processes including neurodegenerative syndromes. In Drosophila , an array of AMPs are produced downstream of the Toll and Imd NF-κB pathways in response to infection. Many studies have suggested a role for the Imd pathway and AMPs in aging in this insect, supported by the upregulation of AMPs with aging (so-called “inflammaging”). However, functional studies using RNAi or over-expression have been inconclusive on whether and how these immune effectors impact aging.

Leveraging a new set of single and compound AMP gene deletions in a controlled genetic background, we have investigated how AMPs contribute to aging. Overall, we found no major effect of individual AMPs on lifespan, with a possible exception of Defensin . However, ΔAMP14 flies lacking 14 AMP genes from seven families display a reduced lifespan. Interestingly, we found an increased bacterial load in the food medium of aged ΔAMP14 flies, suggesting that the lifespan reduction of these flies was due to a failure in controlling the microbiome. Consistent with this idea, use of germ-free conditions extends the lifespan of ΔAMP14 flies. Overall, our results do not point to an overt role of individual AMPs in lifespan. Instead, we find that AMPs collectively impact lifespan by preventing dysbiosis over aging. This is consistent with our previous study showing that AMPs control the gut microbiome, and many works showing that dysbiosis is detrimental upon aging. In the course of our experiments, we also uncovered a strong impact of a Drosophila nora virus infection on lifespan, and share our experience in reconciling our data given this confounding cryptic factor.

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  1. Version published to 10.1101/2022.08.24.504952v3 on bioRxiv
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    Reply to the reviewers

    2RE: Review Commons Refereed Preprint #RC-2022-01651

    Overall author response to reviewers:

    We appreciate the enthusiasm of reviewer 3, who remarks on how our study’s toolset allows us to tackle a longstanding question in the field. We also appreciate the fair criticisms of reviewers 1 and 2.

    We have taken into account all the comments of the reviewers by adding new data and new figures, but also by better underlining the limitations of our study design. Here, we underline the main points (see below for points to points answer).

    We have addressed the reviewer’s concerns by including sex-specific data in the supplemental for each figure. We also hope the reviewers can see the value in not making this manuscript about sex-specific lifespan effects given our arguments below. We believe that additional experiments using a co-housing design, with far more replication per sex per genotype, would be needed to make strong claims about sex-specific effects. In designing our study, we included both sexes to avoid biasing our overall results to only one sex. In our study, we did not design our experiments in a way that allows sex*genotype interactions to be distinguished from vial effects. We believe our current evidence is sufficient to make claims strictly at the genotype level. But at the sex-specific level, not only is our study not designed for a fair comparison of the sexes by virtue of keeping them in independent vials (with independent microbiomes developing over long timeframes), but such comparisons would also be less robust, effectively based on only half the data per treatment compared to comparisons at the genotype level.

    Of note, we do report Cox mixed model statistics in the figures for the interested reader. We just focused on median lifespans for data presentation clarity, and to ensure we focused only on strong trends we could be confident were not statistical Type I errors (falsely rejecting a true null hypothesis). While relying on median lifespan for insights is non-standard, focusing on and showing median lifespans also allows us to better display inter-experiment variation by showing individual data points reflecting each experiment. Sum survival curves with error bars/shading would force us to make an arbitrary decision about what error range to display (SE? SD? 95%CI?), and would not permit the reader to see inter-experiment variation. Median lifespan graphs also let us show just how repeatable our experiments were. We also chose to analyse median lifespan to make it easier to consider the effect of multiple hypothesis testing, so we could better ensure that trends in our data are really striking enough to be worth comment, particularly given the genetics caveats we draw attention to (despite our isogenization efforts, e.g. DefSK3).

    We hope with the revisions we provide, reviewers 1 and 2 can, if not agree, at least acknowledge our concern with claiming many sex*genotype interactions. Such effects are lost if we look at other genotypes containing those mutations (e.g. GrA vs. GrAC, or GrB vs. GrBC). It is a challenge to use the fly lines we have generated, which systematically combines 8+ mutant loci, requiring constant reflection. Taking into consideration the complexities of life span studies, we prefer to focus our attention only on the key and robust results of our study.

    Nevertheless, in the revised version, we also now provide additional data, and we soften our language regarding the impact of nora virus on aging. We have included new data with additional genotypes that were nora-infected to reinforce our claim that nora virus impacts lifespan. These data greatly strengthen the correlation of nora virus and lifespan reduction. We now also make it explicit that our statement that nora virus infection shortens lifespan is strictly correlation-based, and does not reflect intentional infection experiments. Of note, our study confirms a previous observation done by Ayebed et al. (2009) in the lab of Dan Hultmark, though we find a more striking effect in the DrosDel iso w1118 background.

    Overall, we believe we have reinforced the claims of our manuscript after the revisions and addressed the constructive comments of the reviewers. Changes from the original manuscript are highlighted in yellow.

    Reviewer #1 (Evidence, reproducibility and clarity (Required)):

    Summary:

    Whether and how age-associated immune hyperactivation affects the ageing process is a key question in the ageing and immunology fields. Using a CRISPR-based knockout approach, Hanson and Lemaitre address the effect of antimicrobial peptides (AMPs), essential immune effectors, on the ageing process. They compared the lifespan and climbing ability of flies deficient for groups of, or individual, AMPs to their isogenic control and the null mutants of the major immune pathways IMD and Toll. Although deletion of individual AMPs had limited effects, the authors detected an association between deletion of a group of AMPs on bacterial proliferation, and examined possible causality using antibiotic treatment. Interestingly, this causal link was missing in the IMD deficient strain, suggesting a potential AMP-independent mechanism of innate immune signalling in the ageing process. The topic is ambitious and exciting; however, the work has some quite serious technical limitations that would need to be addressed with further data analysis and experimentation.

    We appreciate Reviewer 1 and Reviewer 2’s concerns regarding the sex-specific effects, which is an important consideration in aging studies. We de-emphasized sex specific effects for reasons outlined in the supplemental text, which we will reiterate here: Per experiment, per genotype, we used ~20 males in one vial and ~20 females in another vial. As a result, the interaction of sex*experiment within a genotype is effectively the same as vial effects. We have to be especially careful of vial effects in our study because we are studying immune-deficient flies susceptible to stochastic microbiome dysbiosis, causing vial stickiness and mass mortality events. Moreover, these mass mortality events are not randomly distributed over aging: they were most likely to occur on Mondays. This is because microbes accrue in the vial over 3 days during the weekend, but only over 2 day time periods for flies flipped between Monday-Friday. As a result, in genotypes that suffer dysbiosis (many AMP group mutants), dysbiosis vial effects can change that experiment’s male/female relative lifespan by ~7 days just by stochastic chance. This issue likely affects other aging studies less, as microbiome dysbiosis is a uniquely important consideration in our immune-deficient flies, and we emphasized this point by noting mass mortality events in Figure 3 as “{“ annotations in the survival curves. We have added these considerations in the revised version (new lines 209-214).

    Microbe density in vials is also affected by remaining fly density. As an example of how this can greatly impact the final data at the sex*genotype level: let’s say 4 males died or were censored over the first 50 days randomly in a given experiment. That male vial (16 flies) is less dense than its paired female vial (20 flies), and would have persistent lower microbe load every flip as fewer flies are transferring microbes to the next vial through feces. Then on say… day 60 (a Monday) of that experiment there’s a mass mortality event. Specifically, at day 60 the female vial, which is more densely populated and has had days-to-weeks of higher microbe transfer rate during flipping, has 11/20 females die at once. On the other hand, the males pull through without mass mortality owing to their lower vial density. Suddenly, the female median lifespan in that experiment is 60. The male mortality is most likely to pass the median the next Monday, when another microbiota-induced mass mortality event occurs. Exactly when these critical weekends occurred was stochastic by experiment, but the fact that they occurred was consistent in all experiments in AMP mutant stocks. In this example, female median lifespan would be 60, while males would likely be 67 or so… Importantly, this isn’t a genuine sex-specific effect, it’s variance from how early stochastic mortality affects late-experiment vial density due to microbiome development. It is a vial effect that can look like a sex*genotype effect given our study design, which is exacerbated here because we work on immune deficient flies given that can exhibit microbiome dysbiosis (Marra et al., 2021; mBio).

    Given the importance of AMPs in combatting infection, we chose to keep sexes separate to avoid random mating, which can introduce stochastic sexually-transmitted infections. We would also then have had to worry about differences in mating rate amongst genotypes impacting the likelihood of transmitting infections, and differently imposing stress on females by having constant suitors even when they were not receptive. A future study using a co-housing setup would be better equipped to tackle microbiome vial effects. We have now performed the study with sexes kept separately, that can provide a reference for that future study. A future study would also benefit from focusing on fewer genotypes, with far more replication per sex per genotype, to ensure AMP*sex*lifespan effects were robust.

    We have now provided supplementary analyses of the genotype-specific ratios of male/female lifespans for each figure (new Table S1-S4). By using the ratio of male lifespan to female lifespan, we focus on how within-genotype comparisons work. We want to emphasize the stochasticity of this ratio depending on experiment batch, even within genotype. For instance, the iso w1118 wild-type male/female lifespan ratio was 0.87 for the six experiment in Figure 2, or 0.93 for the four experiments in Figure 3. It’s a reminder that any collection of experiments is just a sampling of the true population mean. Still, we do see some striking departures in the paper from these ratios. For instance, if we focused on striking departures from this sexual dimorphism, we could comment on a couple genotypes in Figure 3 (AMP groups figure): Group B had a ratio of 1.04 (Only females had reduced lifespan, while males remained comparable to iso w1118). Yet in Group AB the ratio is 0.91, with both sexes having proportionally reduced lifespan. And then Group BC, the ratio is 0.86, with both sexes living to wild-type lifespans. ∆AMP10 and ∆AMP14, which contain all Group B mutations, also have ratios of 0.87 and 0.93 respectively. We also did not see a striking effect in individual mutations from Group B, which all have lifespan and male/female ratios comparable to wild-type. What are we to make of Group B alone then? Is it a genuine effect that combining the Group B mutations uniquely reduces female lifespan? Or is this simply an outlier, perhaps caused by vial effects, that is not supported by all other individual or combinatory genotypes that include Group B mutations?

    With all that said, the supplemental tables now included for each figure note these data trends, and includes our cautious view of how to best interpret them. We prefer to merge the sexes in the main article to simplify data display, which is not unique to our study (e.g. see Kounatidis et al. 2017; Cell Rep). We feel our study is not robust at the sex*genotype level to make assertions on sex-specific effects.

    Major comments:

    1. Figure 1A shows a large increase in fly lifespan in response to deletion of 8 AMPs on Chr II. However, the labelling on the figure shows that data from different experimental runs and from the two sexes have been combined to produce the result, and this problem runs through subsequent results. This is not an acceptable approach. Males and females have different average lifespans and may respond differently to the deletion. Repeats of the same lifespan measurement at different times often give significantly different absolute lifespans between runs, even if the differences between experimental treatment are consistent. The procedure used to construct this Figure therefore lumps heterogeneous data, which in this case is both biologically and, more generally, statistically invalid. We need to see an analysis where the results for the sexes and for different runs of the experiment are disaggregated. To assess the effect of the deletion, comparison should be made only within a single replicate of the experiment, and within each sex. It needs to be made clear how many experimental runs were done and with how many flies in each, since replicability is important with these labile traits. Data should be appropriately analysed, for instance with Log Rank test, or, if the assumptions of the test are fulfilled, with Cox Proportional Hazards. The authors mention analysis of median lifespans, but it is not clear what experimental data the medians were derived from, and this is not a gold standard approach to analysis of lifespan data. This problem also applies to the comparison made between lifespans of iso w1118 flies in Figure 1A and 1B - these were evidently measured in different experiments, so direct comparison cannot be made.

    We hope the above response reassures the reviewer about our statistical approach, which we agree is non-standard. We feel it is less likely to result in false-positive claims (Type I error) given the many genotypes we screen and the high stochasticity of individual vials affecting some AMP mutant genotypes more than others (i.e. statistically: unequal variance, requiring an alternate data treatment). Still, we did perform Cox mixed models, and we report those genotype-specific p-values in the figures. But we prefer to make inferences only based on trends robust enough to show in median lifespan comparisons.

    1. Figure 2A reports data from mutants that were not backcrossed into a standard genetic background. The authors were aware that this can be a problem because they took care of it with their own mutants, but the data reported in this Figure 2A could be entirely attributable to difference in genetic background between stocks rather than the mutants themselves.

    Agreed. The reviewer may be confused regarding our intent in showing these genotypes. We used lines as used in other papers to show how control genotypes behave in our hands. This makes our study easier to compare to the broader literature encompassing immunity*aging studies. The intent is not to test if those mutations’ effects are true in another background. They are there to provide context for our lab settings compared to other studies. They are inter-study calibrator controls.

    We have added some text in the study to better highlight the utility of including these control genotypes for making our work more comparable for the field at large (e.g. Line 298, Line 515).

    1. Sexual dimorphism is widely reported in many ageing and immunology studies (reviewed in Belmonte et al., Front. Immunol., 2020 and Garschall et al., F1000Res., 2018). This is a problem for the data discussed on line 317, where it is suggested that Group A mutations are shorter lived than the control group because Group A carries the DefSK3 mutation. However, if the results are split by sex, the lifespan difference between Group A vs control is solely contributed by the shorter-lived male flies in Group A. The female flies in Group A live as long as the female control flies. However, the lifespans of both genders of the DefSK3 mutant in Figure 2B are all shorter than control flies. There appears to be a complicated interaction, with diverse function of individual AMPs during ageing, which cannot be summarised by the statement that "deleting single AMP genes has no effect on lifespan" on line 295.

    The reviewer is correct that Group A shows a male-specific lifespan reduction. But taking the example of Group B above, we could argue that Group B uniquely reduces female lifespan; except when Group B mutations are found alone, or small combinations (e.g. Dro-AttAB, DptSK1), or in the Group AB, Group BC, ∆AMP10, and ∆AMP14 backgrounds. The same contradictory results are true of the Group A result the reviewer highlights, as Group AC has the opposite effect on male/female lifespan ratios and wild-type lifespan, and ∆AMP10 and ∆AMP14 have normal male/female lifespan ratios.

    1. The authors claimed nora virus regulates fly lifespan but they do not produce any direct evidence that this is the case. Bleaching can remove many bacteria and viruses, including many pathogens. To establish the causal role of nora virus on lifespan, reinfection studies with a range of microbes including nora virus would be needed.

    We absolutely agree. These experiments were not intended to test for the effect of nora at the outset. Nora is only highlighted because its presence is strictly correlated, in our hands, with strongly reduced lifespan and also the bloating phenotype seen upon aging. We did not previously show other nora-infected data in the manuscript, but in retrospect, we can see that additional context is needed to reassure the reader of why we suspect nora so strongly. We have modified Figure 1B to include nora-positive data from four additional genotypes that were infected with nora at various times in the lab (previously did not show).

    To explain the process of how we detected nora in some of our AMP stocks: we randomly screened them for a set of common viruses as part of a research workshop in 2019 hosted by Luis Teixeira. The results of that initial screen were not formally recorded, though we screened all the individual and group AMP mutants available at the time. The viruses we screened for were: Drosophila sigma virus, DCV, DAV, and Drosophila nora virus. Out of the stocks relevant to this study (~20 genotypes), we detected nora virus in iso w1118, AttC, Group C, and Bom. The new data we provide even includes an experiment where AttC with/without nora was included at the same timeframe (re: batch effect concern). We also had instances where OR-R became newly infected with nora virus just from random lab inoculation (not intentional infection).

    Importantly, we had noted AttC, Group C and Bom as lines with exceptionally poor lifespan that also showed a bloating phenotype upon aging for ~2 years before we had nora virus on our radar. We were operating on a hypothesis of cryptic microsporidia infection at the time based on a set of chitin stainings of hemolymph that didn’t fully pan out. What convinces us this is nora virus and not a co-infecting virus/microbe is that we only saw the reduced lifespan and bloating upon aging in these confirmed nora-positive lines out of the ~20 we were screening at the time: a 5/5 correlation. We were even able to go back and screen RNA collected from those stocks from earlier experiments to confirm nora infection (informing which experiments we could objectively censor from our analyses). Upon bleaching, we rescued the lifespan of iso w1118, AttC, Bom, and Group C to the levels reported in the main figures. We hope this adds weight to the correlation between nora and lifespan, even if we haven’t done proper reinfection experiments. We also thank the reviewers for commenting, as including these data improves our study by providing more context on the variability of the nora lifespan effect in different genotypes: for instance, we did not collate the nora-infected OR-R data previously, but upon analyzing those data, the negative effect is clearly present but to a lesser extent than iso w1118 (and more in line with what was seen in Habayeb et al. (2009)).

    To address the reviewer’s comment, we have also softened our language to be very clear we find only an association, and do not provide a demonstration (new lines 191-193). But the results were sufficiently striking, and poor lifespan associated with bloating was perfectly predictive of nora presence in stocks in our hands. We fully believe the result and feel it is important to include this in the main text to make the field more aware of this important aging study confounding variable.

    1. The authors reported a potential AMPs-independent mechanism of the IMD/Relish pathway on ageing, which would be important. However, in Figure 4A and the associated raw data, the authors compared the lifespans of flies from different experiments, and this seems to be a problem. Using ΔAMP14 as an example of a more general problem: the authors assayed conventional feeding ΔAMP14 flies between 07.2021 and 11.2021; however, the antibiotic treated flies were assayed between 12.2021 and 02.2022. There is an obvious batch effect: the median lifespan of ΔAMP14 is 50d on 29.07.2021, 73d on 20.08.2021, 65d on 06.11.2021, and 61d on 10.11.2021. There is therefore a confounding of batch effects with the biological function of AMPs. Some groups seem to have extremely limited sample size, such as only two female flies and six male flies were recorded in "ATM8 23-07-2021 f" in Figure 2A-associated raw data.

    We show this inter-experiment variation explicitly by presenting individual experiments as data points in median lifespan graphs. It is not hidden, it is emphasized by our median lifespan data presentation style. The experiments from 06.11.2021 and 10.11.2021 were from independently kept stocks of ∆AMP14, although naturally they come from similar timeframes and would have used food prepared at roughly the same time. If the reviewer feels we should merge the two experiments, we can do that. Merging the experiments and having only 3 entered replicates for conventionally-reared ∆AMP14 changes the one-way ANOVA result in Fig. 4B from “p = .006” to “p = .004,” so we don’t feel having those two experiments entered independently is biasing the analysis. We do feel the parents, and the flies measured, were independent at the rearing level.

    ATM8 specifically had poor homozygous viability. This is the only genotype with such a significant departure in sample size per experiment. ATM8 flies are also not relevant to the core message of the study, and their reduced lifespan was extremely clear and in line with previous studies. We prefer to keep the genotype in the study to allow comparison of our lab conditions to studies using ATM8. We have added this note in the Fig. 2 caption (Line 1029).

    Regarding how much can be attributed to batch effects: there are many elements of laboratory studies that can contribute to batch effects. However antibiotic food would undergo independent food preparation from standard food regardless of what we do, and parents and flies would be reared in independent vials from independent food preps regardless of what we do. This really just leaves the seasons as the batch effect, which ought to be controlled for by our incubators controlling temperature and humidity. We do appreciate the valid concern, and that incubators aren’t perfect. But we want the importance of the concern to be viewed in the light that even had we done the experiments at the same time, the conventionally-reared and antibiotic-reared flies would still have been given totally different preparations and conditions. Given this consideration, we will further note:

    1. ∆AMP14 flies were already known to suffer dysbiosis with aging (Marra et al., 2021; mBio). Our present study only quantifies the effect of this dysbiosis on lifespan.

    2. Dysbiosis is associated with flies gut barrier dysfunction and gut content leakage into the hemolymph (Rera et al., 2012; PNAS)(Clark et al., 2015; Cell Rep).

    3. Imd-mediated barrier dysfunction leads to microbiome invasion into the hemolymph (Buchon et al., 2009; Genes Dev).

    4. Systemic infection by microbiota-derived Acetobacter kills AMP mutants (Marra et al., 2021; mBio)(Hanson et al., 2022; Proc R Soc B), which suggests microbiome invasion into the hemolymph will kill AMP mutants more readily than wild-type flies.

    The result that AMP mutants have improved lifespan in antibiotic conditions is therefore not especially surprising – it is important to actually test this, but it is by no means unexpected. One of the curious findings of our study is that we could not rescue Relish to the same extent. If batch effects were affecting the antibiotic rescue experiments by having different intrinsic lifespans during those months, we would expect this to also be visible in iso w1118 and Relish. Antibiotics (or time period batch effects) did not affect lifespan of our wild-type flies, which was very repeatable across all experiments across many years, agreeing with antibiotic-reared fly data from Ren et al. (2007).

    Minor comments:

    1. The authors reported that the mutant flies lacking 14 AMPs are short-lived due to dysbiosis. Interestingly antibiotic treatment rescued the shortened lifespan of ΔAMP14 but not RelE20. Considering that some of these AMPs, such as lDef, Dro and Drs, are controlled by both the IMD and Toll pathways. It would be worth exploring if the axenic environment could improve the lifespan of Toll mutant flies, which might point to a distinct function of the Toll pathway on the microbiome and ageing process.
    2. Line 169: The authors stated that they screened the existence of common viruses but did not provide the results.
    3. Line 179: The authors need to include the quantitative results of nora virus in their 44 stocks.
    4. Lines 311-314 should be combined with the next paragraph as they are all about "screening".
    5. Line 319: Please indicate the associated panel "Fig. 2B" instead of using "Fig. 2".
    6. Lines 353 and 358 and in Figure 3C: The authors should provide the quantification of the sticky food in AMPs mutant and Relish mutant flies.
    7. Line 389: Please indicate the associated panel "Fig. 2A-B" instead of using "Fig. 2".
    8. Line 435: As discussed above, the authors cannot rule out an effect of individual AMPs on lifespan based on their current data and interpretation.
    9. Line 507: "During our study, we experienced a number of challenges to lifespan data interpretation." As discussed in the major comments, unless the authors re-perform and re-analyse the lifespan assays this problem will persist.
    10. Line 514: As discussed above, the authors cannot rule out the effect of other pathogens on lifespan.

    We appreciate the reviewer’s request for spz axenic lifespans. The effect was more striking in Relish, and so we focused on Relish, which regulates antibacterial peptides in the gut. Repeating the experiment with spz will cause non-essential delays and would not affect our main conclusions that focus on AMPs genes.

    Line 179: we have, in Fig. 1C. Negatives are not shown, but positives are included in the “Stocks” column. Is the reviewer requesting the exact stock names? We can provide most of these… although the screen was organized by having lab members submit stocks that were in use, and so the spreadsheet of those results is organized with labels provided by lab members (e.g. FM1, rather than the genotype exactly). So we cannot provide exactly which stocks were positive in our hands, but we also don’t feel this is important for the reader. We can share the spreadsheet of this screen (conducted in Dec 2020) with the reviewer if desired.

    We were happy to revise the manuscript according to all other requests/comments, highlighted in yellow, and hope our explanations above are sufficient to give the full weight and meaning of the statement in Line 507.

    Reviewer #1 (Significance (Required)):

    Significance: The crosstalk between AMPs and ageing is a long-standing contradictory topic in the immunology and ageing field (Loch et al., PLoS One, 2017; Badinloo et al., Arch. Insect Biochem. Physiol., 2018; Garschall et al., F1000Res., 2018). This work is a potential step in determining whether and how AMPs regulate ageing. This research may open a door toward yet uncharacterized AMP-independent mechanisms of innate immune signalling in the ageing process.

    I am familiar with Drosophila ageing and its relationship with innate immunity, although I am not an insect immunologist.

    Reviewer #2 (Evidence, reproducibility and clarity (Required)):

    Summary: In this study, Hanson and Lemaitre generated AMP single or compound mutants, and subjected them to lifespan analyses. They showed that deletion of all AMPs but not individually (except for Defensin) reduced Drosophila lifespan. The observations that ΔAMP14 suffered microbial dysbiosis and antibiotic treatment rescued the decreased lifespan in ΔAMP14 flies implied a link between AMP-controlled lifespan and host microbiome. Thus, the authors would like to conclude that AMPs contribute to fly lifespan via modulating microbiome.

    Comments: This reviewer deeply appreciates that the authors generated AMP mutants (individually or with various combinations). However, these mutants have been reported in their previous publications (eLife, 2019; Genetics, 2021). It seems that the authors carefully analyzed the lifespan of indicated flies, but many pieces of data are inconsistent with previous findings (for instance the lifespan under axenic condition). The explanation about the fly medium (Line 476-477) is not convincing (if yes, who not analyze the lifespan using the same diet as described in previous studies?). The lifespan analyses are of course the most pivotal part in this study, but it is a pity that the results are not shown in an appropriate way, making them rather difficult to interpret. For example, the reviewer is surprised to note that the lifespan of males and females are not analyzed and shown separately (e.g. Figures 1A, 1B, 2A, 2B, 3A, 4A), even the authors declared that they did this before lifespan examination. It is also unclear how many males and females were utilized individually in most assays.

    We do not believe the axenic lifespans are inconsistent with previous findings. There have been papers both finding an effect of antibiotics, or finding no effect of antibiotics, on wild-type flies (ex: refs 56 and 57: Ren et al., 2007 and Brummel et al., 2004). Our study would support no major effect. Given our note on nora virus, one might wonder if papers where antibiotics affected lifespan might in part be explained by pathogens (like viruses) that were confounding results in the initial stock, and cleared by the initial bleaching common to those experiments. This would imply that commensal bacteria/fungi community do not have a major role in wild-type lifespans, but rather some stocks are stochastically infected with opportunistic viral pathogens, giving the impression that antibiotic treatment was the key, when in fact it was the bleaching pre-treatment that removed an opportunistic viral pathogen. This is only speculation, but it emphasizes the importance of openly discussing the effect nora virus can have on lifespan for future studies.

    Regarding the diet comment: which standard diet should we have chosen? There are many standard diets. We have provided our recipe and we have used our diet for decades. Of note, we did try a set of experiments on a molasses-based food, which showed similar lifespan for wild-type flies in our hands (Response supplemental figure below).

    We hope our answers to the first reviewer regarding our care to not include sex*genotype interactions as major claims in our study will satisfy reviewer 2’s concerns.

    SEE ATTACHED RESPONSE TO REVIEWERS FOR FIGURE

    Response supplemental figure: rearing on molasses food (recipe per lab of Brian McCabe) does not drastically alter wild-type lifespan. In this pilot experiment (n = 1) iso w1118 and OR-R lifespan remain comparable to our standard diet, including the relative lifespans of those wild-types to each other.

    Another weakness is the study regarding AMP and microbiome. The authors observed that both ΔAMP14 and RelE20 flies became sticky during aging and their foods in the vials were also sticky and discolored, implying the proliferation of microbiome in the gut and/or the external environment of these flies. To test the microbial load, the authors performed an assay of the bacterial abundance on the fly medium. They further performed antibiotic treatment in the food to remove microbiome as they declared in the study and examined the effect on the lifespan of ΔAMP14 flies. According to the knowledge of the reviewer, antibiotic treatment in food can restrict the microbiome in the gut. The authors have also mentioned in the manuscript the important role of gut microbiota in impacting Drosophila aging and lifespan. Thus, a more direct and widely-utilized way is to dissect the guts for microbial analysis (qPCR, 16S-seq, etc.), which is lacking in this study without reasonable explanations.

    We published a paper in mBio on the relationship of AMPs and the microbiome with aging in much greater detail previously (Marra et al., 2021; mBio, ref25). That study did not perform lifespan experiments, but rather compared microbiome communities at 10 and 29 days. The novel aspect of this study is properly following survival. However, the reviewer is correct in their critique that our study is not especially innovative nor are our findings strikingly novel. We do have, we feel, an important set of experimental results to contribute to the field at large.

    Reviewer #2 (Significance (Required)):

    This study utilized various AMP mutants, but these mutants have been reported in the previous publications, making this study somehow lacking the novelty in this context. The IMD pathway has been shown to be involved in regulating fly lifespan, so the findings in this study are not that surprising. Additionally, this study doesn't show any creative improvements in terms of methodology and model system.

    Admittedly, in some ways, much of our study is a “negative results” study. Given the contradictory nature of the literature claiming positive or negative effects of immunity and AMPs on lifespan, we feel this is a particularly valuable contribution to avoid publication bias focusing only on significant results in this controversial field. Still, we believe that the AMP/microbiome/lifespan interactions we uncover in our article will have an impact in the immune-aging field. Thus, while not being fully creative, our article is an important step for better characterizing of immune-aging relationships, which is of broad interest.

    Reviewer #3 (Evidence, reproducibility and clarity (Required)):

    Gene knockouts provide definitive loss of function for individual and collective AMPs. This eliminates ambiguity caused by the partial efficiency of RNAi, and it disambiguates the pleiotropy caused by mutants of relish. Survival assays are conducted with and without the resident microbiome. This combined design leads to a clear conclusion: loss if individual (mostly so) AMPs does not affect adult survival either way, demonstrating these peptides likely function redundantly. Knock out of 14 AMPs (but still not all of those encoded in the genome) reduces survival when adults must cope with a microbiome. Depleting this microbiome sends survival back to normal. Perhaps these are not surprising results in that they show immune function is essential when challenged with pathogens, but the results are important because they unambiguously show that AMPs themselves are not a cause of intrinsic aging. This will finally put away that lingering hypothesis.

    Overall, I like the scholarship of the work, of how it uses the literature, and its quality experimental execution. Cohort size, replication and survival analyses meet current, high standards. Demographic aging is supplemented with data on climbing rate as a function of age. It is a strength of the study that it is simple but comprehensive.

    Reviewer #3 (Significance (Required)):

    Aging across animal systems is strongly associated with changes in immunity and inflammation, both innate and adaptive. Overall, we want to understand if such changes are underlying causes of morbidity and mortality with age, or are consequences and compensation to underlying aging and cumulative pathogen exposure. These are difficult questions to address in mammalian systems but amenable using Drosophila which possesses a robust innate immune system. Researchers have used the fly for this end but still have mixed and ambiguous results. Now Hanson and Lemaitre provide a substantial design that fully controls the two essential ingredients: expression of antimicrobial peptides and the microbiome.

    We thank the reviewer for their positive assessment. In particular, we appreciate the nod to the importance of the question on intrinsic contributions of AMPs to lifespan. We believe this is the key strength of our study’s mutant approach, which has been challenging to assess using previously-existing tools.

    Additional Author changes (not requested by reviewers):

    We realised there was a copy/paste error in data used in Figure 2. Specifically, extra OR-R experiments were included in these data for this figure that were not intended to be part of this figure. We have removed these OR-R experiments, which are experiments common to Figure S4 and remain visible in Figure S4. This does not impact any of the conclusions in the manuscript.

  3. Review Commons

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    Referee #3

    Evidence, reproducibility and clarity

    Gene knockouts provide definitive loss of function for individual and collective AMPs. This eliminates ambiguity caused by the partial efficiency of RNAi, and it disambiguates the pleiotropy caused by mutants of relish. Survival assays are conducted with and without the resident microbiome. This combined design leads to a clear conclusion: loss if individual (mostly so) AMPs does not affect adult survival either way, demonstrating these peptides likely function redundantly. Knock out of 14 AMPs (but still not all of those encoded in the genome) reduces survival when adults must cope with a microbiome. Depleting this microbiome sends survival back to normal. Perhaps these are not surprising results in that they show immune function is essential when challenged with pathogens, but the results are important because they unambiguously show that AMPs themselves are not a cause of intrinsic aging. This will finally put away that lingering hypothesis.

    Overall, I like the scholarship of the work, of how it uses the literature, and its quality experimental execution. Cohort size, replication and survival analyses meet current, high standards. Demographic aging is supplemented with data on climbing rate as a function of age. It is a strength of the study that it is simple but comprehensive.

    Significance

    Aging across animal systems is strongly associated with changes in immunity and inflammation, both innate and adaptive. Overall, we want to understand if such changes are underlying causes of morbidity and mortality with age, or are consequences and compensation to underlying aging and cumulative pathogen exposure. These are difficult questions to address in mammalian systems but amenable using Drosophila which possesses a robust innate immune system. Researchers have used the fly for this end but still have mixed and ambiguous results. Now Hanson and Lemaitre provide a substantial design that fully controls the two essential ingredients: expression of antimicrobial peptides and the microbiome.

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    Referee #2

    Evidence, reproducibility and clarity

    Summary:

    In this study, Hanson and Lemaitre generated AMP single or compound mutants, and subjected them to lifespan analyses. They showed that deletion of all AMPs but not individually (except for Defensin) reduced Drosophila lifespan. The observations that ΔAMP14 suffered microbial dysbiosis and antibiotic treatment rescued the decreased lifespan in ΔAMP14 flies implied a link between AMP-controlled lifespan and host microbiome. Thus, the authors would like to conclude that AMPs contribute to fly lifespan via modulating microbiome.

    Comments:

    This reviewer deeply appreciates that the authors generated AMP mutants (individually or with various combinations). However, these mutants have been reported in their previous publications (eLife, 2019; Genetics, 2021). It seems that the authors carefully analyzed the lifespan of indicated flies, but many pieces of data are inconsistent with previous findings (for instance the lifespan under axenic condition). The explanation about the fly medium (Line 476-477) is not convincing (if yes, who not analyze the lifespan using the same diet as described in previous studies?). The lifespan analyses are of course the most pivotal part in this study, but it is a pity that the results are not shown in an appropriate way, making them rather difficult to interpret. For example, the reviewer is surprised to note that the lifespan of males and females are not analyzed and shown separately (e.g. Figures 1A, 1B, 2A, 2B, 3A, 4A), even the authors declared that they did this before lifespan examination. It is also unclear how many males and females were utilized individually in most assays.

    Another weakness is the study regarding AMP and microbiome. The authors observed that both ΔAMP14 and RelE20 flies became sticky during aging and their foods in the vials were also sticky and discolored, implying the proliferation of microbiome in the gut and/or the external environment of these flies. To test the microbial load, the authors performed an assay of the bacterial abundance on the fly medium. They further performed antibiotic treatment in the food to remove microbiome as they declared in the study and examined the effect on the lifespan of ΔAMP14 flies. According to the knowledge of the reviewer, antibiotic treatment in food can restrict the microbiome in the gut. The authors have also mentioned in the manuscript the important role of gut microbiota in impacting Drosophila aging and lifespan. Thus, a more direct and widely-utilized way is to dissect the guts for microbial analysis (qPCR, 16S-seq, etc.), which is lacking in this study without reasonable explanations.

    Significance

    This study utilized various AMP mutants, but these mutants have been reported in the previous publications, making this study somehow lacking the novelty in this context. The IMD pathway has been shown to be involved in regulating fly lifespan, so the findings in this study are not that surprising. Additionally, this study doesn't show any creative improvements in terms of methodology and model system.

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    Referee #1

    Evidence, reproducibility and clarity

    Summary:

    Whether and how age-associated immune hyperactivation affects the ageing process is a key question in the ageing and immunology fields. Using a CRISPR-based knockout approach, Hanson and Lemaitre address the effect of antimicrobial peptides (AMPs), essential immune effectors, on the ageing process. They compared the lifespan and climbing ability of flies deficient for groups of, or individual, AMPs to their isogenic control and the null mutants of the major immune pathways IMD and Toll. Although deletion of individual AMPs had limited effects, the authors detected an association between deletion of a group of AMPs on bacterial proliferation, and examined possible causality using antibiotic treatment. Interestingly, this causal link was missing in the IMD deficient strain, suggesting a potential AMP-independent mechanism of innate immune signalling in the ageing process. The topic is ambitious and exciting; however, the work has some quite serious technical limitations that would need to be addressed with further data analysis and experimentation.

    Major comments:

    1. Figure 1A shows a large increase in fly lifespan in response to deletion of 8 AMPs on Chr II. However, the labelling on the figure shows that data from different experimental runs and from the two sexes have been combined to produce the result, and this problem runs through subsequent results. This is not an acceptable approach. Males and females have different average lifespans and may respond differently to the deletion. Repeats of the same lifespan measurement at different times often give significantly different absolute lifespans between runs, even if the differences between experimental treatment are consistent. The procedure used to construct this Figure therefore lumps heterogeneous data, which in this case is both biologically and, more generally, statistically invalid. We need to see an analysis where the results for the sexes and for different runs of the experiment are disaggregated. To assess the effect of the deletion, comparison should be made only within a single replicate of the experiment, and within each sex. It needs to be made clear how many experimental runs were done and with how many flies in each, since replicability is important with these labile traits. Data should be appropriately analysed, for instance with Log Rank test, or, if the assumptions of the test are fulfilled, with Cox Proportional Hazards. The authors mention analysis of median lifespans, but it is not clear what experimental data the medians were derived from, and this is not a gold standard approach to analysis of lifespan data. This problem also applies to the comparison made between lifespans of iso w1118 flies in Figure 1A and 1B - these were evidently measured in different experiments, so direct comparison cannot be made.
    2. Figure 2A reports data from mutants that were not backcrossed into a standard genetic background. The authors were aware that this can be a problem because they took care of it with their own mutants, but the data reported in this Figure 2A could be entirely attributable to difference in genetic background between stocks rather than the mutants themselves.
    3. Sexual dimorphism is widely reported in many ageing and immunology studies (reviewed in Belmonte et al., Front. Immunol., 2020 and Garschall et al., F1000Res., 2018). This is a problem for the data discussed on line 317, where it is suggested that Group A mutations are shorter lived than the control group because Group A carries the DefSK3 mutation. However, if the results are split by sex, the lifespan difference between Group A vs control is solely contributed by the shorter-lived male flies in Group A. The female flies in Group A live as long as the female control flies. However, the lifespans of both genders of the DefSK3 mutant in Figure 2B are all shorter than control flies. There appears to be a complicated interaction, with diverse function of individual AMPs during ageing, which cannot be summarised by the statement that "deleting single AMP genes has no effect on lifespan" on line 295.
    4. The authors claimed nora virus regulates fly lifespan but they do not produce any direct evidence that this is the case. Bleaching can remove many bacteria and viruses, including many pathogens. To establish the causal role of nora virus on lifespan, reinfection studies with a range of microbes including nora virus would be needed.
    5. The authors reported a potential AMPs-independent mechanism of the IMD/Relish pathway on ageing, which would be important. However, in Figure 4A and the associated raw data, the authors compared the lifespans of flies from different experiments, and this seems to be a problem. Using ΔAMP14 as an example of a more general problem: the authors assayed conventional feeding ΔAMP14 flies between 07.2021 and 11.2021; however, the antibiotic treated flies were assayed between 12.2021 and 02.2022. There is an obvious batch effect: the median lifespan of ΔAMP14 is 50d on 29.07.2021, 73d on 20.08.2021, 65d on 06.11.2021, and 61d on 10.11.2021. There is therefore a confounding of batch effects with the biological function of AMPs. Some groups seem to have extremely limited sample size, such as only two female flies and six male flies were recorded in "ATM8 23-07-2021 f" in Figure 2A-associated raw data.

    Minor comments:

    1. The authors reported that the mutant flies lacking 14 AMPs are short-lived due to dysbiosis. Interestingly antibiotic treatment rescued the shortened lifespan of ΔAMP14 but not RelE20. Considering that some of these AMPs, such as lDef, Dro and Drs, are controlled by both the IMD and Toll pathways. It would be worth exploring if the axenic environment could improve the lifespan of Toll mutant flies, which might point to a distinct function of the Toll pathway on the microbiome and ageing process.
    2. Line 169: The authors stated that they screened the existence of common viruses but did not provide the results.
    3. Line 179: The authors need to include the quantitative results of nora virus in their 44 stocks.
    4. Lines 311-314 should be combined with the next paragraph as they are all about "screening".
    5. Line 319: Please indicate the associated panel "Fig. 2B" instead of using "Fig. 2".
    6. Lines 353 and 358 and in Figure 3C: The authors should provide the quantification of the sticky food in AMPs mutant and Relish mutant flies.
    7. Line 389: Please indicate the associated panel "Fig. 2A-B" instead of using "Fig. 2".
    8. Line 435: As discussed above, the authors cannot rule out an effect of individual AMPs on lifespan based on their current data and interpretation.
    9. Line 507: "During our study, we experienced a number of challenges to lifespan data interpretation." As discussed in the major comments, unless the authors re-perform and re-analyse the lifespan assays this problem will persist.
    10. Line 514: As discussed above, the authors cannot rule out the effect of other pathogens on lifespan.

    Significance

    The crosstalk between AMPs and ageing is a long-standing contradictory topic in the immunology and ageing field (Loch et al., PLoS One, 2017; Badinloo et al., Arch. Insect Biochem. Physiol., 2018; Garschall et al., F1000Res., 2018). This work is a potential step in determining whether and how AMPs regulate ageing. This research may open a door toward yet uncharacterized AMP-independent mechanisms of innate immune signalling in the ageing process.

    I am familiar with Drosophila ageing and its relationship with innate immunity, although I am not an insect immunologist.

  6. Version published to 10.1101/2022.08.24.504952v1 on bioRxiv
  7. Version published to 10.1101/2022.08.24.504952v2 on bioRxiv