Animals associate with communities of microorganisms, also known as their microbiome, that live in or on their bodies. Within these communities, microbes – such as yeast and bacteria – interact by producing chemical compounds called metabolites that can influence the activity of other members of the community. These metabolites can also affect the host, helping with nutrition or causing disease.

The behavior of an animal may help it to acquire its microbiome, although this has not been properly explored experimentally. For example, the fruit fly Drosophila melanogaster acquires members of its microbiome from the microbes found on the fermented fruit that it eats. It is possible that the flies – and other animals – respond to microbial metabolites, which act as signals or cues that cause the animal to avoid or seek the microbial community.

The fruit fly microbiome is commonly studied in the laboratory because it has a much simpler composition than mammalian microbiomes. Previous studies have explored how the flies respond to odors produced by individual types of microbes, but none have explored how the behavior of the flies changes in response to the odors produced by a mixed microbial community.

Fischer et al. now show that fruit flies are preferentially attracted to microbiome members that are interacting with each other. The flies detected members of the microbiome by responding to chemicals that are only produced when community members grew together. For example, one member of the microbial community produces ethanol that is then converted to acetate by another community member. Neither ethanol nor acetate alone attracted flies as strongly.

Fischer et al. also discovered that both adult fruit flies and their larvae benefit from acquiring a mixture of different microbes at the same time. Adult flies benefit by avoiding harmful concentrations of either ethanol or acetic acid, and larvae benefit from developing in an environment that reduces how quickly disease-causing microbes can grow.

Overall, the results presented by Fischer et al. detail how flies select a beneficial, interactive microbiome from an external reservoir of microorganisms. Flies also have internal mechanisms, like their immune system, that help them to select their microbiome. Therefore a future challenge will be to integrate the behavioral and internal selection mechanisms into a single model of microbiome acquisition.

Multispecies microbial communities (microbiomes) influence animal biology in diverse ways (McFall-Ngai et al., 2013): microbiomes modulate disease (van Nood et al., 2013), metabolize nutrients (Zhu et al., 2011), synthesize vitamins (Degnan et al., 2014), and modify behavior (Bravo et al., 2011). A central goal in host-microbiome studies is to understand the molecular mechanisms underpinning these diverse microbiome functions.

Some aspects of microbial community function are the product of inter-species interactions (Rath and Dorrestein, 2012; Manor et al., 2014; Gerber, 2014; Gonzalez et al., 2012). For example, microorganisms modulate the metabolomes of neighboring species (Derewacz et al., 2015; Jarosz et al., 2014) and microbial metabolites (e.g., antibiotics) alter bacterial transcriptional responses (Goh et al., 2002). Despite current understanding of microbial inter-species interactions in vitro, some of which has been elucidated in exquisite detail, the consequences of microbial interspecies interactions within host-associated microbiomes are just beginning to be explored experimentally.

Insight into host-associated microbiome function has stemmed mostly from whole-microbiome [e.g., re-association of germ-free hosts with whole microbiomes (Ridaura et al., 2013) and modeling microbiome function based on gene annotation (Costello et al., 2009)] or single-microorganism [e.g., re-association of germ-free hosts with a single microorganism (Ivanov et al., 2009)] studies. However, these approaches tend to reveal only limited insight into inter-species microbial interactions, which can provide hosts with essential services. For example, termite symbionts carry genes necessary for metabolism of different parts of complex carbohydrates (Poulsen et al., 2014), yet their function has not been demonstrated in vivo; co-occurring human gut symbionts share polysaccharide breakdown products cooperatively (Rakoff-Nahoum et al., 2014, 2016), but the consequences of such interactions for the host are unknown; inter-species bacterial interactions protect Hydra from fungal infection (Fraune et al., 2015), but the mechanism of host protection is unclear. The need to understand the effects of inter-species microbiome interactions motivated our current work.

Attractive model systems in which to study the outcomes of inter-species microbial interactions for host biology would include a tractable host that harbors a simple multispecies microbiome. Here, we report the use of Drosophila melanogaster to study interactions in a simple microbiome and their consequences for host behavior.

The Drosophila microbiome consists largely of yeasts, acetic acid bacteria, and lactic acid bacteria (Chandler et al., 2011, 2012; Broderick and Lemaitre, 2012; Camargo and Phaff, 1957; Staubach et al., 2013). Drosophila ingests microbiome members from the environment (e.g., fermenting fruit, [Camargo and Phaff, 1957; Barata et al., 2012; Erkosar et al., 2013; Blum et al., 2013; Broderick et al., 2014]), a behavior posited as a mechanism for Drosophila to select, acquire, and maintain its microbiome (Broderick and Lemaitre, 2012; Blum et al., 2013). Drosophila behavior toward environmental microorganisms has focused on yeasts (Becher et al., 2012; Christiaens et al., 2014; Schiabor et al., 2014; Palanca et al., 2013; Venu et al., 2014). Yeasts attract Drosophila via ester production (Christiaens et al., 2014; Schiabor et al., 2014), induce Drosophila egg-laying behavior (Becher et al., 2012), and are vital for larval development (Becher et al., 2012). Lactic and acetic acid bacteria produce metabolites (e.g., acids) that may repel Drosophila at high acid concentrations, while also inducing egg-laying preference for sites containing acetic acid (Ai et al., 2010; Joseph et al., 2009). One motivation of our study was to analyze Drosophila behavior toward the yeast and bacteria that dominate the Drosophila microbiome.

Yeast and bacteria are largely studied within separate Drosophila sub-disciplines, despite their shared habitat (Broderick and Lemaitre, 2012). Yeasts serve as food, providing Drosophila vitamins, sterols, and amino acids (Broderick and Lemaitre, 2012). Lactic and acetic acid bacteria are gut microbiome members (Wong et al., 2011) promoting larval development (Shin et al., 2011; Storelli et al., 2011), increasing resistance to pathogens (Blum et al., 2013), inducing intestinal stem cell proliferation (Buchon et al., 2009), and reducing adult sugar and lipid levels (Newell and Douglas, 2014; Wong et al., 2014). Since microorganisms that are traditionally considered ‘food’ co-exist with those considered ‘microbiome’ in fruit fermentations and the two groups provide Drosophila with different resources, we hypothesized that Drosophila might detect a beneficial community via metabolites that are produced cooperatively by the desirable symbionts. Alternatively, Drosophila might detect a different metabolite as the signal for each symbiont.

Fruit undergoes a well-characterized ripening process in which cell-wall degrading enzymes and amylases convert the firm, starchy tissue into soft, sugar-rich fruit (El-Zoghbi, 1994; Abu-Goukh and Bashir, 2003; Mao and Kinsella, 1981). The high sugar content supports microbial colonization and fermentation by Drosophila-associated microorganisms, including yeasts, lactic acid bacteria, and acetic acid bacteria (Barata et al., 2012; Barbe et al., 2001). Drosophila avoids ‘green’ fruit and is attracted to ‘overripe’ fruit (Turner and Ray, 2009), yet it is unclear how Drosophila behavior is influenced by the dynamic multispecies fruit microbiome and its metabolic properties. To this end, we developed a model fruit fermentation system that afforded measurement of microbial populations, microbial metabolites, and Drosophila behavior.

Here we demonstrate the importance of emergent microbiome metabolism—quantitatively different or unique metabolites produced by the microbiome, but not by any of its members in isolation—on behavior, suggesting that Drosophila larvae and adults benefit by behaviorally selecting a multispecies, interactive microbiome.

To determine whether Drosophila responds to emergent microbial community metabolites, we used the T-maze olfactory assay to analyze Drosophila behavioral responses to several Drosophila microbiome members grown individually or in communities (Figure 1A, Supplementary file 2, Figure 1—figure supplement 1). When the strains were grown individually, Drosophila was strongly attracted to yeasts, moderately attracted to acetic acid bacteria, and neutral or slightly repelled by lactic acid bacteria (Figure 1B,C). Because strains within a microbial group attracted Drosophila similarly, a representative yeast, acetic acid bacterium, and lactic acid bacterium were used to test the effect of interactions between microbiome members on Drosophila behavior. Drosophila preferred microbial communities grown together to microorganisms grown individually and then mixed prior to analysis (defined throughout as a separate-culture mixture, Figure 1D). Focusing on a model Saccharomyces cerevisiae and Acetobacter malorum community, we found that when tested against apple juice medium (AJM), Drosophila attraction to the community was stronger than to the separate-culture mixture or individual members (Figure 1E). In sum, Drosophila detects, and prefers, microorganisms growing together to a mixture of the same strains combined after they had completed growth.

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Raw Drosophila preference data for Figure 1B,C.

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Raw Drosophila preference data for Figure 1D.

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Raw Drosophila preference data for Figure 1E.

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We next measured the attractiveness and other properties of the co-culture over time. When grown alone, the microorganisms had similar growth profiles (Figure 2A). However, when grown with A. malorum, S. cerevisiae populations first increased, then decreased between 60 and 72 hr, and were undetectable by 96 hr (Figure 2A). The decrease in S. cerevisiae viable counts mirrored a decrease in pH (Figure 2—figure supplement 1A). Drosophila did not prefer the co-culture relative to the separate-culture mixture at 34 hr; however, Drosophila was more attracted to the co-culture from 48–127 hr (Figure 2B). Moreover, the Drosophila attraction to the 96 hr co-culture was stronger than its preference for the 48, 54, or 60 hr co-cultures (Figure 2B). Drosophila preference for the co-culture correlated with lower pH and S. cerevisiae population density, despite Drosophila olfactory avoidance of acid (Ai et al., 2010) and reliance on yeast for nutrition (Anagnostou et al., 2010) (Figure 2C,D). Drosophila preference did not correlate with viable A. malorum populations (Figure 2—figure supplement 1B). Drosophila preference for the co-culture increased relative to sterile media during 34–96 hr of growth, which is consistent with the increase in Drosophila attraction being due to a property of the co-culture rather than to a decrease in attraction to the separate-culture mixture (Figure 2—figure supplement 1C). Moreover, Drosophila was more attracted to the 72 hr co-culture than individual cultures or the separate-culture mixture at any other growth stage (i.e. 24, 34, 72 hr; Figure 2—figure supplement 1D,E). In sum, several properties of the microbial community (e.g. S. cerevisiae density, pH) parallel Drosophila detection of, and preference for, the co-culture.

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Raw Drosophila preference data, microbial population data, and pH data for Figure 2A,C,D & Figure 2—figure supplement 1A,B.

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Mutants in broadly and narrowly tuned ionotropic and olfactory receptors [Irs and Ors, respectively, (Abuin et al., 2011; Hallem and Carlson, 2006)] were used to evaluate the role of Drosophila olfactory reception in discriminating the co-culture from the separate-culture mixture during and immediately following peak attraction (Figure 3—figure supplement 1). During the most attractive phase of the co-culture (e.g. 67–115 hr), homozygous mutants of Drosophila ORCO and Or42b showed a significant reduction in attraction to the co-culture, whereas no role was detected for Drosophila homozygous mutants in several Irs or Or35a (Figure 3A). As co-culture growth proceeded (e.g. 139–163 hr), attraction decreased and the role of Or42b and ORCO waned (Figure 3). An independent homozygous mutant of ORCO also showed reduced attraction to the co-culture, whereas the heterozygotes ORCO/+ and Or42/+ were attracted to the co-culture similarly to wild-type flies (Figure 3B).

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ORCO is a required co-receptor for all other Or gene products (Larsson et al., 2004) and Or42b, one of the most conserved olfactory receptors, detects esters and 1,1-diethoxyethane (Mathew et al., 2013; Asahina et al., 2009; Stökl et al., 2010). These results suggest that Or42b enables Drosophila to distinguish the co-culture from the separate-culture mixture. Moreover, a non-ORCO factor explains ~40% of Drosophila co-culture preference (Figure 3A,B). Previous work found that ORCO is fully responsible for the Drosophila attraction to apple cider vinegar (Semmelhack and Wang, 2009), suggesting that the behavioral circuit activated by inter-species interactions between S. cerevisiae and A. malorum is distinct from the circuit activated by apple cider vinegar.

We speculated that the emergent property of co-culture attractiveness might arise from a distinct metabolic profile of the co-culture. Using gas chromatography-mass spectrometry (GC-MS), we identified volatiles unique to or differentially produced in the co-culture compared to the separate-culture mixture. Five co-culture volatiles (ethanol, isobutanol, isoamyl alcohol, acetic acid, isoamyl acetate) were confirmed with standards (Table 1—source data 1 and 2) and quantified with standard curves (Table 1—source data 3 and 4). The alcohol concentrations were lower, and acetic acid and isoamyl acetate were unique in the co-culture relative to the other experimental groups (Table 1). The molecular profile was reminiscent of ethanol catabolism as the unique co-culture metabolic process. We therefore hypothesized that ethanol catabolism was the emergent metabolic process.

We next measured ethanol and acetic acid levels over time (24–156 hr) and compared the chemical dynamics to Drosophila preference. Consistent with a relationship between ethanol catabolism, acetic acid anabolism, and Drosophila attraction, the dynamics of Drosophila co-culture preference mirrored ethanol depression and acetic acid accumulation in the co-culture (Figure 4A). Furthermore, as ethanol catabolism and acetic acid anabolism proceeded (36–96 hr), Drosophila attraction toward the co-culture increased until 96 hr, at which point it decreased, consistent with lower turnover of ethanol at the end of ethanol catabolism (Figure 4A, black line).

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Raw spectral abundance data associated with metabolites graphed in Figure 4A.

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Raw Drosophila preference data for Figure 4B.

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Raw Drosophila preference data for Figure 4C.

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We hypothesized that Drosophila preferred the community during peak ethanol turnover (e.g. co-cultures at ~72 hr of growth) compared with the community during pre-ethanol catabolism (e.g. co-culture at ~36 hr of growth) or during late-stage ethanol catabolism, in which ethanol turnover is low (e.g. co-culture at ~144 hr of growth; Figure 4A). Consistent with our hypothesis, Drosophila preferred the co-culture in the middle stage of ethanol catabolism to earlier or later stages of ethanol catabolism (Figure 4B). To test directly whether ethanol catabolism underpinned Drosophila co-culture preference, we evaluated Drosophila preference for the co-culture harboring a mutant in adhA, which encodes pyrroloquinoline quinone-dependent alcohol dehydrogenase (PQQ-ADH-I), the enzyme that converts yeast-derived ethanol into acetaldehyde on path to acetic acid (Shin et al., 2011). Co-cultures using either A. malorum or A. pomorum wild-type (WT) along with S. cerevisiae were equally attractive to Drosophila (Figure 4—figure supplement 1). Drosophila preferred the co-culture containing A. pomorum WT versus a separate-culture mixture; however, Drosophila did not prefer the co-culture containing A. pomorum adhA versus a separate-culture mixture (Figure 4C). Moreover, Drosophila preferred the co-culture containing A. pomorum WT to the co-culture containing A. pomorum adhA (Figure 4C). In sum, ethanol catabolism is necessary for Drosophila to discriminate between the co-culture and the separate-culture mixture.

We next identified additional metabolites unique to the co-culture using solid-phase microextraction gas chromatography-mass spectrometry (SPME GC-MS). Acetic acid, six acetate esters, an acetaldehyde metabolic derivative (acetoin), a putative acetaldehyde metabolic derivative (2,4,5-trimethyl-1,3-dioxolane), and two unknown metabolites were more abundant in the co-culture relative to the separate-culture mixture or co-culture with A. pomorum adhA (Table 2, Table 2—source data 1–6). To determine the molecular basis for Drosophila co-culture preference, select metabolites were added to the co-culture containing A. pomorum adhA. Esters and acetic acid, but not esters alone, were sufficient to fully restore the attractiveness of the co-culture containing A. pomorum adhA to the co-culture containing A. pomorum WT levels (Figure 4C).

Although acetate and its metabolic derivatives were sufficient for Drosophila co-culture preference, acetaldehyde is a reactive intermediate during ethanol catabolism whose metabolic derivatives might be increased in microbial communities compared with individual microbial cultures. Consistent with this idea, acetoin was moderately increased in the co-culture compared with the separate-culture mixture (Table 2—source data 1); strikingly, acetoin was increased ~27 fold in the tri-culture (S. cerevisiae, A. malorum, and L. plantarum) compared to the co-culture (Figure 5A,B, Figure 5—figure supplement 1) and was attractive to Drosophila (Figure 5C). In sum, emergent metabolites from two- and three-membered communities, including acetaldehyde metabolic derivatives, attract Drosophila.

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Extracted ion current for m/z 88.05 in Figure 5A.

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Peak areas associated with acetoin for Figure 5B.

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Raw Drosophila preference data for Figure 5C.

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To further investigate the potential role of acetaldehyde and its metabolic derivatives in Drosophila behavior, we performed a dose response in which acetaldehyde was added to the separate-culture mixture (Figure 6—figure supplement 1A) to evaluate its ability to induce attractiveness to co-culture levels. Even at the lowest tested levels, acetaldehyde supplementation stimulated the separate-culture mixture to attractiveness levels equal to the co-culture (Figure 6—figure supplement 1A). Three acetaldehyde metabolic derivatives—acetoin, 1,1-diethoxyethane (an acetal), and 2,3-butanedione—were sufficient to induce the attractiveness of the separate-culture mixture to levels equivalent to the co-culture containing A. pomorum WT using concentrations of each metabolite at or below the physiological concentration of acetoin found in the tri-culture (Figure 6—figure supplement 1B).

A pure metabolite mixture comprised of key metabolic groups produced by microbial communities and identified in this study (esters, acetaldehyde metabolic derivatives, alcohols, acid) attracted Drosophila similarly to the co-culture (Figure 6A,B). Interestingly, the acetaldehyde metabolic derivatives alone were sufficient to attract Drosophila similarly to the co-culture (Figure 6C). Moreover, removal of the acetaldehyde metabolic derivatives group alone reduced Drosophila attraction (Figure 6D). In sum, acetaldehyde metabolic derivatives are potent Drosophila attractants.

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Concentrations of mixtures and raw Drosophila preference data for Figure 6.

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Overall, our results suggest that both esters and acetaldehyde metabolic derivatives are keystone microbial community metabolites that attract Drosophila. We next created a simple 9-metabolite mixture in water (containing only one acid, four esters, and four acetaldehyde metabolic derivatives) and measured Drosophila preference toward this mixture in relation to the yeast-acetic acid bacteria co-culture, the yeast-acetic acid bacteria-lactic acid bacteria microbial community, or apple cider vinegar (ACV). The defined mixture used concentrations for each acetaldehyde metabolic derivative similar to the concentration of acetoin in the tri-culture and ester and acid concentrations that were in the range detected in the co-culture. The defined 9-metabolite mixture was more attractive than all other conditions (Figure 6—figure supplement 2). In sum, acetaldehyde metabolic derivatives and esters are potent Drosophila attractants whose detection may signal the presence of actively metabolizing, multispecies microbial communities.

We hypothesized that Drosophila preference for communities during peak ethanol turnover reflected fitness benefits derived from ingesting metabolites associated with different staged communities. To test this hypothesis, we measured adult Drosophila survival when given ethanol and acetic acid concentrations characteristic of microbial cultures at different stages of ethanol catabolism. Adult Drosophila survival was highest when given metabolites associated with middle-staged ethanol catabolism compared with pre- or end-stage ethanol catabolism (Figure 7—figure supplement 1A). In sum, Drosophila preference provides benefits associated with consumption of microbial community-generated metabolites.

Next, we explored the relationship between Drosophila attraction and egg-laying preference. Drosophila preferred to lay eggs in the co-culture containing A. pomorum WT to the co-culture containing A. pomorum adhA (Figure 7A). Therefore, we predicted that Drosophila larvae would develop more quickly in the wild-type condition than the adhA condition. In contrast, we found that larvae develop more slowly when consuming the co-culture containing A. pomorum WT compared with the co-culture containing A. pomomrum adhA (Figure 7B). This result may be explained by the fact that A. pomorum WT kills the nutritious yeast cells, whereas the A. pomorum adhA mutant does not (Figure 7—figure supplement 1B). Given the role of yeast in Drosophila development (Becher et al., 2012) the co-culture containing A. pomorum adhA, which supports yeast populations, may be more nutritive for developing Drosophila larvae than the co-culture containing A. pomorum WT.

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Raw Drosophila egg-laying preference data for Figure 7A.

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Raw developmental data for Figure 7B,C,E,F.

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Another potential selective pressure on the choice of egg-laying sites is the presence of pathogens and parasites. The presence of parasitoid wasps increases Drosophila egg deposition in high ethanol concentration sites, which are protective to larvae (Rollero et al., 2015). Drosophila also avoids laying eggs in habitats containing pathogenic molds by detecting geosmin (Stensmyr et al., 2012). Additionally, acetic acid, a unique metabolite in the co-culture containing A. pomorum WT, inhibits phytopathogenic fungi (Kang et al., 2003). To test whether the co-culture containing A. pomorum WT protects developing larvae from environmental fungi, we allowed Drosophila to lay eggs in co-culture containing S. cerevisiae and either A. pomorum WT or A. pomorum adhA and quantified the total number of eggs, pupae, and adults. We found that Drosophila laid significantly more eggs in the co-culture containing A. pomorum WT than the co-culture containing A. pomorum adhA (Figure 7C). Following open-air exposure to environmental microbes, unidentified fungi grew on the co-cultures containing A. pomorum adhA, but did not grow on the co-cultures containing A. pomorum WT (Figure 7D). Furthermore, more pupae and adults survived in the co-culture containing A. pomorum WT compared to the co-culture containing A. pomorum adhA (Figure 7E,F). In sum, Drosophila egg-laying preference in the co-culture containing A. pomorum WT may reflect an underlying benefit in fungal pathogen defense.

Here, we have demonstrated how emergent properties of a microbial community—volatile profile, population dynamics, and pH—influence Drosophila attraction, survival, and egg-laying behaviors. Our study is the first to identify the consequences of microbe-microbe metabolic exchange on animal behavior and discovers additional microbial interactions that attract Drosophila for further mechanistic study (Figure 1D).

Microbe-microbe metabolic exchange generates unique and quantitatively different volatiles from those resulting from individual microbial metabolism (Table 1 and 2, Figure 8). Acetobacter-generated acetate coupled to Saccharomyces-derived alcohols spawn diverse acetate esters (Table 1 and 2). We hypothesize that more complex and diverse communities, comprising alcohol-producing yeasts, acetate-producing Acetobacter, and lactate-producing Lactobacillus, will generate a wider array of attractive esters (Figure 8). The community of S. cerevisiae, A. malorum, and L. plantarum emitted higher levels of acetoin and attracted Drosophila more strongly than the co-culture of S. cerevisiae and A. malorum (Figure 1D, Figure 5). Acetoin and 2,3-butanedione are formed by an α-acetolactate intermediate in bacteria and directly from acetaldehyde in yeast (Chuang et al., 1968). We therefore hypothesize that communities of yeasts and bacteria may emit high levels of attractive acetaldehyde metabolic derivatives (Figure 8).

Figure 8

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Previous studies have found that yeasts alone can produce esters in high concentrations (Becher et al., 2012; Christiaens et al., 2014; Schiabor et al., 2014). In this study, we found that S. cerevisiae produced low quantities of esters when grown alone. One explanation for the low ester production is that in contrast to previous studies that have used more complex media, we used an apple juice medium that is much lower in nitrogen content. Nitrogen content positively correlates with the yeast ester production (Becher et al., 2012; Rollero et al., 2015). Our results suggest that environmental nitrogen availability might predict microbial ester production and Drosophila attraction. In high nitrogen environments, yeasts likely produce ester compounds and strongly attract Drosophila. However, in low nitrogen environments Acetobacter may be responsible for ester production and Drosophila attraction; Acetobacter may be capable of producing esters in low nitrogen conditions or may generate locally high nitrogen environments by assimilating nitrogen from yeast killed by its production of acetic acid. Future work should determine the relationship in wild fruit fermentations between nitrogen content and ester production by yeasts and bacteria.

Drosophila behavioral studies have mostly focused on yeasts. Yeasts attract Drosophila and are the preferred substrate for Drosophila to lay eggs (Becher et al., 2012). However, we find that Drosophila attraction toward the co-culture increases as yeast viability declines (Figure 2). One reason why Drosophila might be attracted to the co-culture as yeast populations decline is that yeasts provide essential nutrients. As such, the lysis of viable yeast by Acetobacter may benefit Drosophila through the liberation of nutrients. An alternative explanation is that in their interaction with Drosophila, Acetobacter may have benefited by evolving to produce esters that in other contexts (e.g. high nitrogen environments) are produced by yeasts. The contribution of Drosophila-associated bacteria to Drosophila behavior is not as well understood as yeasts (Venu et al., 2014). Our results suggest that non-yeast microorganisms, especially when grown in microbial communities, affect Drosophila behaviors. We reason that additional studies that couple chemical microbial ecology with Drosophila behavior will herald the discovery of additional microbe-influenced behaviors and microbial community-generated metabolites.

This study demonstrates the coordination of ethanol synthesis and catabolism by S. cerevisiae and Acetobacter, respectively, and the role of ethanol in Drosophila behavior and survival. Non-Saccharomyces Drosophila microbiome members also make ethanol (Ruyters et al., 2015) and diverse acetic acid bacteria catabolize ethanol, generalizing our findings to other microbial community combinations. Ethanol can have deleterious or beneficial fitness consequences for Drosophila depending on concentration (Ranganathan et al., 1987; Azanchi et al., 2013) and ecological context (Kacsoh et al., 2013). Our results are consistent with Drosophila using products of inter-species microbiome metabolism to detect a community that titrates ethanol concentration optimally for the host. Work that further dissects the consequences of acetic acid and ethanol concentrations on Drosophila biology and investigates other community-level metabolic profiles will be of interest to enrich the chemical and ecological portrait of the Drosophila microbiome.

Drosophila egg-laying preference for the co-culture containing A. pomorum WT may provide a fitness tradeoff for the host. On the one hand, we observed that juice agar plates inoculated with the co-culture containing A. pomorum WT had fewer viable yeast cells and larvae developed more slowly, likely due to the lower vital nutrients (e.g. protein, vitamins) than would be available in the co-culture containing A. pomorum adhA. On the other hand, when exposed to environmental microbes, juice agar plates inoculated with the co-culture containing A. pomorum WT were not invaded by fungi, whereas the co-culture containing A. pomorum adhA was susceptible to fungal growth. This suggests that in more natural conditions the catabolism of ethanol into acetic acid, which delays larval development in the microbial community studied here (e.g. in a community with S. cerevisiae), ultimately has a protective effect. Whether this is due to a direct elimination of pathogens or instead indirectly limits fungal competition, as has been shown for dietary yeasts and Aspergillus sp. (Rohlfs and Kürschner, 2010) is unknown. Future work that more thoroughly dissects the Drosophila fitness tradeoffs that result from its association with different microbiomes is of interest.

Our work raises questions about the consequences of the observed behavior on microbiome assembly and stability in the Drosophila intestine. Drosophila possesses specific and regionalized gut immune responses to the microbiome (Lhocine et al., 2008; Ryu et al., 2008; Paredes et al., 2011; Costechareyre et al., 2016) implying a tolerant environment in which privileged microbiome members are maintained and reproduce in the Drosophila intestine. Other work suggests that Drosophila acquires its adult microbiome from exogenous sources, that adult microbiome abundance drops without continuous ingestion of exogenous microorganisms, and that the microbiome can be shaped by diet (Chandler et al., 2011; Blum et al., 2013; Broderick et al., 2014). As such, a combination of internal mechanisms, exogenous factors, and host behavior likely sculpt the microbiome; determining the relative contribution of each will be important moving forward. Complicating our understanding of the contribution of these factors is the opaque distinction between ‘microbiome’ and ‘food’, since both are ingested from the environment (Broderick, 2016). To dissect the formation and stability of the Drosophila microbiome, the fate of ingested microorganisms needs to be monitored and microbial intestinal replication needs to be surveyed as a function of Drosophila behavior, age, immune status, microbiome membership, and nutritional state [e.g. using synthetic diets without yeast; (Shin et al., 2011; Piper et al., 2014)].

In sum, our results support a model in which the Drosophila olfactory system is tuned to fruity (e.g., esters) and buttery (several acetaldehyde metabolic derivatives, such as 2,3-butanedione) smelling metabolites promoted by microbe-microbe interactions. We anticipate that accounting for microbial interactions in diverse host-microbe studies will lead to new insights into diverse aspects of microbial-animal symbioses.

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Author details

1. Caleb N Fischer

   Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, United States

   Present address

   Department of Chemistry, Vanderbilt University, Stevenson Center, Nashville, United States

   Contribution

   CNF, Conception and design, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0003-4223-8511

2. Eric P Trautman

   Department of Chemistry, Yale University, New Haven, United States

   Contribution

   EPT, Acquisition of data, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

3. Jason M Crawford

   Department of Chemistry, Yale University, New Haven, United States

   Contribution

   JMC, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-7583-1242

4. Eric V Stabb

   Department of Microbiology, University of Georgia, Athens, United States

   Contribution

   EVS, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

5. Jo Handelsman

   Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, United States

   Contribution

   JH, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   Competing interests

   The authors declare that no competing interests exist.

6. Nichole A Broderick

   1. Department of Molecular, Cellular and Developmental Biology, Yale University, New Haven, United States
   2. Department of Molecular and Cell Biology, University of Connecticut, Storrs, United States
   3. Institute for Systems Genomics, University of Connecticut, Storrs, United States

   Contribution

   NAB, Conception and design, Analysis and interpretation of data, Drafting or revising the article

   For correspondence

   nichole.broderick@uconn.edu

   Competing interests

   The authors declare that no competing interests exist.

   "This ORCID iD identifies the author of this article:" 0000-0002-6830-9456

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