Animals detect food primarily through taste and olfactory systems. Across phyla, there is enormous complexity in olfactory receptors and downstream processing mechanisms that allow for detection and differentiation between odorants (Keller et al., 2017; Nara et al., 2011; Parnas et al., 2013). By contrast, taste coding is thought to be simpler, with most animals possessing fewer taste receptors and a diminished ability to differentiate between tastants (Freeman and Dahanukar, 2015; Scott, 2018; Yarmolinsky et al., 2009). Most early studies in different species have focused on characterization of a limited number of taste modalities largely defined by human percepts (sweet, bitter, sour, umami, salt), though there is growing appreciation that additional taste pathways are likely to influence gustatory responses and feeding (Chaudhari and Roper, 2010; Scott, 2018). Between studies of Drosophila and mammals, cells or receptors that are involved in sensing water, carbonation, fat, electrophiles, polyamines, metal ions, and ribonucleotides have been identified, suggesting a previously underappreciated complexity in the coding of tastants (Cameron et al., 2010; Kang et al., 2010; Mishra et al., 2018; Zhang et al., 2013). Elucidating the underlying mechanisms of tastant detection can provide fundamental insight into the molecular and cellular basis of tastant recognition and taste processing.

In flies and mammals, tastants are sensed by dedicated gustatory receptors that are expressed in gustatory receptor neurons (GRNs) or taste cells, respectively. In both systems, distinct subsets of taste sensory cells are responsive to compounds belonging to distinct taste modalities such as sweet or bitter, and convey information to discrete areas of higher order brain structures (Vosshall and Stocker, 2007; Yarmolinsky et al., 2009; Zhang et al., 2003). Given the conserved logic of taste processing, flies provide a powerful system for studying sensory processing and principles of taste circuit function (Freeman and Dahanukar, 2015; Scott, 2018; Yarmolinsky et al., 2009). Further, a number of genes and biochemical pathways that regulate feeding behavior are conserved across phyla (Vosshall and Stocker, 2007; Yarmolinsky et al., 2009). Notably, the gustatory system of Drosophila is amenable to in vivo Ca²⁺ imaging and electrophysiology, both of which can be coupled with robust behavioral assays that measure reflexive taste responses and food consumption (Wisotsky et al., 2011). Taste neurons are housed in gustatory sensory structures called sensilla, which are located in the distal segments of the legs (tarsi), in the external and internal mouth organs (proboscis and pharynx), and in the wings. Each sensillum contains dendrites of multiple GRNs, each of which can be distinguished from the others based on its responses to various categories of tastants. Two main classes of non-overlapping gustatory neurons that have been identified are sweet-sensing and bitter-sensing neurons. Sweet-sensing GRNs promote feeding, whereas bitter-sensing GRNs act to deter (Marella et al., 2006; Thorne et al., 2004). Both sweet and bitter GRNs express subsets of 68 G-protein-coupled gustatory receptors (GRs) (Clyne et al., 2000; Scott et al., 2001). In addition, the Drosophila genome encodes 66 glutamate-like ionotropic receptors (IRs), a recently identified family of receptors implicated in taste, olfaction, and temperature sensation (Benton et al., 2009; Rytz et al., 2013). GRNs predominantly project to the subesophageal zone (SEZ), the primary taste center, but the higher order circuitry downstream of the SEZ contributing to taste processing is poorly understood (Flood et al., 2013; Marella et al., 2012; Pool et al., 2014; Wang et al., 2004). Determining how tastants activate GRNs that convey information to the SEZ and how these signals are transmitted to higher order brain centers is central to understanding the neural basis for taste and feeding.

In Drosophila, GRNs in the labellum and tarsi detect hexanoic acid (Masek and Keene, 2013). Mutation of ionotropic receptor 56d (IR56d) disrupts hexanoic acid taste, implicating IR56d as a fatty acid receptor, or as part of a complex involved in fatty acid taste (Ahn et al., 2017; Sánchez-Alcañiz et al., 2018). IR56d is co-expressed with GR64f (Ahn et al., 2017; Tauber et al., 2017), which broadly labels sweet GRNs (Dahanukar et al., 2007; Jiao et al., 2008; Slone et al., 2007). IR56d-expressing GRNs are responsive to both sugars and fatty acids, suggesting that these neurons may respond to diverse appetitive substances including multiple classes of fatty acids (Tauber et al., 2017). Notably, overlapping populations of sweet GRNs are responsive to different appetitive modalities and confer feeding behavior.

Are flies capable of differentiating between tastants of the same modality or is discrimination within a modality exclusively dependent on intensity? Taste discrimination can be assayed by training flies by pairing a negative stimulus with an appetitive tastant and determining whether the acquired aversion generalizes to another tastant (Keene and Masek, 2012; Masek and Scott, 2010). A previous study employing such experiments found that flies are unable to discriminate between different sugars (Masek and Scott, 2010). Conversely, we reported that flies can discriminate between sucrose (sugar) and hexanoic acid (fatty acid), revealing an ability to discriminate between appetitive stimuli of different modalities (Tauber et al., 2017). Here, we find that flies are capable of discriminating between different classes of fatty acids, despite broad tuning of fatty-acid-sensitive neurons to short-, medium-, and long-chain fatty acids.

Sugars and medium-chain fatty acids are sensed by an overlapping population of gustatory neurons, and flies can discriminate between these two attractive tastants (Ahn et al., 2017; Tauber et al., 2017). To test whether flies are capable of discriminating within a single modality, we measured the ability of flies to discriminate between different types of fatty acids of the same concentration. We used an aversive taste memory assay in which an appetitive tastant applied to the proboscis is paired with application of bitter quinine immediately afterwards, resulting in an associative memory that inhibits responses to the appetitive tastant (Masek et al., 2015). A modified version of this assay, in which training with one tastant is followed by testing with another, allows us to determine whether flies can discriminate between these tastants (Figure 1A).

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Raw taste discrimination data between short-, medium-, and long-chain fatty acids.

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We first sought to determine whether flies are capable of differentiating between short- (3C–5C), medium- (6C–8C), and long-chain (>9C) fatty acids. We found that flies that were trained with pairing of quinine and medium-chain hexanoic acid (6C) exhibited proboscis extension response (PER) to subsequent application of short-chain valeric acid (5C; Figure 1B). Thus, aversive memory to 5C was not formed by training with 6C, suggesting that flies can discriminate between these short- and medium-chain fatty acids. Similarly, flies trained with 6C did not generalize aversive memory to 9C, consistent with the idea that flies can also discriminate between medium- and long-chain fatty acids (Figure 1C). To rule out the possibility that flies are unable to form aversive taste memories to short- and long-chain fatty acids, we trained with 5C and found robust aversive taste memory, which did not generalize to 9C (Figure 1D). Together, these results suggest that flies are capable of distinguishing between short-, medium-, and long-chain classes of fatty acids.

To determine whether flies can discriminate between compounds within each class of fatty acid, we tested the ability of flies to differentiate among each short-, medium-, and long-chain fatty acid class. We first trained flies to associate 4C, a short-chain fatty acid, with quinine, while a second short-chain fatty acid, 5C, was not reinforced. We found that the aversive memory formed with 4C was generalized to 5C, suggesting that flies cannot discriminate between different short-chain fatty acids (Figure 1E). Next, we trained flies to associate 6C, a medium-chain fatty acid, with quinine, while the medium-chain fatty acids 7C or 8C were not reinforced. In both cases, flies formed aversive memories to 6C, and these generalized to 7C and 8C, suggesting that flies cannot discriminate between different medium chain fatty acids (Figure 1F, G). To fortify these findings, we trained flies to 7C and measured the response to 8C. Again, flies formed aversive memory to 7C that was generalized to 8C (Figure 1H). Lastly, we trained flies to associate 10C, a long-chain fatty acid, with quinine, while a second long-chain fatty acid, 9C, was not reinforced. We again found that the aversive memory formed with 10C was generalized to 9C, suggesting that flies cannot discriminate among long-chain fatty acids (Figure 1I).

To verify that taste discrimination observed between different classes of fatty acids is not simply the result of prior experience, we performed reciprocal experiments to those in Figure 1, in which the tested tastant was used during training, and the trained tastant was used to assess taste discrimination. Consistent with the findings from the first series of experiments, we found that flies are able to discriminate between short-, medium-, and long-chain fatty acids (Figure 1—figure supplement 1A–C), but are unable to discriminate between fatty acids within a particular class (e.g., medium-chain fatty acids; Figure 1—figure supplement 1D–F). Further, it is possible that repeated presentation of fatty acid may alter the valence of the tastant over time. To address this, we asked whether there were any differences in PER between the pretest, training, and test applications among the naïve groups in each test of taste discrimination. We found that PER to consecutive applications of fatty acid shows no significant change in responsiveness over time, although in some cases PER to fatty acid trends downward (Figure 1—figure supplement 1). Taken together, these results reveal that flies cannot discriminate among different short-, medium-, or long-chain fatty acids, although they are able to discriminate medium-chain fatty acids from short- or long-chain fatty acids.

A potential confounding factor in the taste memory assay used to assess discrimination is that flies may discriminate based on perceived intensity rather than the class identity of fatty acids. To test this possibility, we tested whether flies trained to 1% 6C could discriminate a different fatty acid tested at a different concentration (0.1%). Even under these test conditions, flies remained able to discriminate between short- (5C) and medium-chain (6C) fatty acids as well as between long- (9C) and medium-chain (6C) fatty acids (Figure 1—figure supplement 2A, B). However, conditioning to a medium-chain fatty acid (6C) generalized to another medium-chain fatty acid (8C), suggesting that despite a 10× difference in concentration, flies remain unable to distinguish between medium-chain fatty acids (Figure 1—figure supplement 2C). These results fortify the notion that flies are able to distinguish between short-, medium-, and long chain fatty acids, but not within fatty acids of the same class.

We next sought to determine whether the discrimination observed in female flies is also found in males. PER analysis with a panel of short-, medium-, and long-chain fatty acids revealed that males respond to all fatty acids tested, though the overall responses were generally lower than those observed in females (Figure 1—figure supplement 3). To assess whether male flies are able to discriminate between different classes of fatty acids, we trained flies to a medium-chain fatty acid (6C) and then measured discrimination between 4C (short), 8C (medium), and 9C (long) fatty acids. Similar to results obtained in female flies, males were able to discriminate between 6C and 4C as well as between 6C and 9C, but not between 6C and 8C (Figure 1—figure supplement 4). Therefore, male flies are also able to discriminate different classes of fatty acids, but are not able to distinguish fatty acids within the same class.

The short-, medium-, and long-chain fatty acids that we tested have distinctly different olfactory activation profiles (Hallem and Carlson, 2006), raising the possibility that flies can discriminate between these compounds using a combination of olfactory and gustatory information. To exclude the effects of olfactory input, we surgically ablated the antennae, the maxillary palps, or both structures, and measured the ability of flies to discriminate between a representative tastant from each short-, medium-, or long-chain fatty acid (Figure 2A). All test groups were able to distinguish between sucrose and hexanoic acid, confirming that the ablation itself does not generally impact taste or memory formation (Figure 2B). Further, flies trained to a medium-chain fatty acid (6C) did not generalize aversion to short- (5C) or long-chain (9C) fatty acids, regardless of the absence of one or both olfactory organs (Figure 2C, D). Taken together, our findings reveal an ability of the taste system to encode the identity of different classes of fatty acids.

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Raw taste discrimination data after ablation of olfactory organs.

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In previous work, we reported that IR56d neurons are required for 6C taste (Tauber et al., 2017). The finding that flies cannot discriminate between medium-chain fatty acids raises the possibility that IR56d neurons mediate taste of medium-chain fatty acids, but not short- and long-chain fatty acids. To test this possibility, we silenced IR56d-expressing neurons using the synaptobrevin cleavage peptide tetanus toxin light chain (TNT; Sweeney et al., 1995) and measured PER to multiple classes of fatty acids, including short-, medium-, and long-chain fatty acids (Figure 3A). To control for any non-specific effects of TNT, we compared PER in flies with silenced IR56d-expressing neurons (IR56d-GAL4 > UAS TNT) to flies expressing the inactive variant of TNT in IR56d-expressing neurons (IR56d-GAL4 > UAS impTNT). Consistent with previous findings (Tauber et al., 2017), we observed no effect of silencing IR56d-expressing neurons on PER to sucrose (Figure 3B). Next, we measured PER to a panel of saturated fatty acids ranging from 4C (butanoic acid) to 10C (decanoic acid) in length (Figure 3C). Control flies exhibited a robust PER to all seven fatty acids, revealing that at least at a 1% concentration many diverse classes of fatty acids can trigger this behavioral response. To determine whether IR56d neurons are generally required for detection of fatty acids or selectively required for sensing hexanoic acid, we next measured PER in flies with IR56d-expressing neurons silenced. Silencing IR56d-expressing neurons significantly reduced PER to the three medium-chain fatty acids (6C, 7C, and 8C). Conversely, there was no difference in PER between control and IR56d-silenced flies in response to short-chain (4C and 5C) and long-chain (9C and 10C) fatty acids. Therefore, IR56d-expressing neurons are required for medium-chain fatty acid taste perception, but are dispensable for PER to both short- and long-chain fatty acids.

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Raw data from proboscis extension response experiments to short-, medium-, and long-chain fatty acids.

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Since IR56d is required for taste response to medium-chain, but not short- or long-chain fatty acids, it is possible that other IRs mediate this response. As a first step in identifying which additional receptor(s) may be involved, we measured PER in both IR76b and IR25a mutants to short-, medium-, and long-chain fatty acids as these broadly expressed receptors have been previously found to mediate taste response to medium-chain fatty acids (Ahn et al., 2017). In agreement with these findings, PERs to medium-chain fatty acids were significantly reduced for both the IR76b and IR25a mutants, while PER to sucrose was normal (Figure 3—figure supplement 1). Additionally, we found that PERs to both short- and long-chain fatty acids were also significantly reduced in both mutants, suggesting that both IR76b and IR25a are required for taste response to all three classes tested (Figure 3—figure supplement 1).

The finding that IR56d-expressing neurons are required selectively for PER to medium-chain fatty acids raises the possibility that other subsets of sweet-sensing GR64f-expressing neurons are required for PER to short- (4C, 5C) and long-chain (9C–10C) fatty acids. Alternatively, it is possible that these classes of fatty acids elicit PER through gustatory neurons that are not labeled by GR64f. To differentiate between these possibilities, we silenced GR64f-expressing neurons and measured PER to short-, medium-, and long-chain fatty acids. In agreement with previous findings, silencing of GR64f-expressing neurons significantly reduced PER to sucrose (10 mM) as well as to medium-chain fatty acids (Figure 3D, E). However, we found no significant differences in responses to both short- and long-chain fatty acids between GR64f-silenced (GR64f-GAL4 > UAS TNT) and control (GR64f-GAL4 > UAS impTNT) flies. Therefore, PER elicited by short- and long-chain fatty acids is conferred by neurons that express neither IR56d nor GR64f.

To directly assess whether the IR56d receptor mediates responses to medium-chain fatty acids, we used the CRISPR/Cas9 system to generate an IR56d allele in which a GAL4 element is inserted into the IR56d locus (IR56d^GAL4; Figure 4A), thereby allowing expression of UAS-transgenes under the control of the IR56d promoter. To confirm that the GAL4 knock-in element is indeed expressed in IR56d-expressing neurons, we generated flies carrying both UAS-mCD8:GFP and the IR56d^GAL4 allele (IR56d^GAL4>UAS-mCD8:GFP) and mapped the expression of GFP. Consistent with previous findings, we found GFP expression in labellar neurons that projected axons to both the taste peg and sweet taste regions of the SEZ (Figure 4B–E; Koh et al., 2014; Tauber et al., 2017). In agreement with previous findings from genetic silencing of IR56d-expressing neurons, PER to sucrose did not differ between IR56d^GAL4 and control flies (Figure 4F), suggesting that IR56d^GAL4 is dispensable for response to sucrose. To examine the role of IR56d in fatty acid taste, we measured PER to fatty acids ranging from 4C to 10C in length (Figure 4G). We found that PER to medium-chain fatty acids was disrupted in IR56d^GAL4 flies (6C–8C), whereas PER to short- (4C and 5C) and long-chain fatty acids (9C and 10C) was not affected. Although both the IR56d^GAL4 mutants and the IR56d-silenced flies have reduced response to medium-chain fatty acids, the response of the IR56d mutant flies was relatively lower, likely caused by the complete deletion of the IR56d gene. Flies that were heterozygous for the IR56d deletion (IR56d^GAL4/+) exhibited similar responses to those of control flies for all tastants measured. The observed decrease in PER to medium-chain fatty acids was rescued by transgenic expression of IR56d in the IR56d^GAL4 mutant background (IR56d^GAL4;UAS-IR56d/+), confirming that the behavioral deficit of IR56d^GAL4 flies is in fact due to loss of IR56d function. Similar results were observed in males. Although taste responses were generally lower, PER to sucrose did not differ between IR56d^GAL4 and control flies, but PER to medium-chain hexanoic acid (6C) was significantly lower (Figure 4—figure supplement 1). Therefore, IR56d appears to be selectively required for taste sensing of medium-chain fatty acids.

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Raw data from IR56d^GAL4proboscis extension response experiments.

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In previous work, we found that IR56d-expressing neurons are responsive to both sucrose and hexanoic acid (Tauber et al., 2017). To determine whether other classes of fatty acids can also evoke activity in these neurons and whether their activity is dependent on IR56d, we measured Ca²⁺ responses to a panel of tastants. We expressed the Ca²⁺ sensor GCaMP6.0 under the control of IR56d^GAL4 and measured tastant-evoked activity in the posterior projections (Figure 5A–D, Figure 5—figure supplement 1), which emanate from labellar taste neurons and are both necessary and sufficient for taste perception to medium-chain hexanoic acid (6C; Koh et al., 2014; Tauber et al., 2017). In flies heterozygous for IR56d^GAL4, the labeled neurons were responsive to sucrose and all fatty acids tested, which ranged from 4C to 10C (Figure 5E). Thus, IR56d neurons respond to diverse appetitive stimuli. Flies with a deletion of IR56d (IR56d^GAL4; UAS-GCaMP6.0) lacked responses exclusively to medium-chain fatty acids (6C–8C), while responses to short- (4C and 5C) and long-chain fatty acids (9C and 10C) remained intact (Figure 5F). Consistent with the rescue of behavioral defects, inclusion of an IR56d rescue transgene (IR56d^GAL4; UAS-GCaMP6.0/UAS-IR56d) restored the physiological response to medium-chain fatty acids (Figure 5G). Quantification of the responses to all tastants confirmed that Ca²⁺ responses to 6C–8C fatty acids are disrupted in IR56d^GAL4 flies and restored to levels observed in control flies by expression of UAS-IR56d (Figure 5H). Overall, these results demonstrate that at both behavioral and physiological levels IR56d^GAL4 is required for taste responses to medium-chain fatty acids.

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Raw imaging data from the posterior labellar region in IR56d^GAL4 flies.

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The neurons expressing IR56d project to two distinct regions within the SEZ: a posterior set of projections that overlap with GR64f-expressing neurons and a set of anterior projections that originate from the taste pegs (Koh et al., 2014; Tauber et al., 2017). The two populations appear to differ in function as the posterior population is responsive to both sucrose and hexanoic acid, while the anterior population is responsive to hexanoic acid, but not sucrose (Tauber et al., 2017). It is possible that the anterior neurons are selectively responsive to medium-chain fatty acids, providing a mechanism for taste discrimination. We generated flies labeling IR56d- and GR64f-expressing neurons with different genetically encoded fluorescent reporters (IR56d^GAL4; UAS-RFP; GR64f-LexA > LexAop GFP) and confirmed that IR56d^GAL4 labels both the anterior and posterior projections (Figure 6A–C). To selectively measure fatty acid responses in anterior taste peg neurons, we expressed UAS-GCaMP6 with a genetic intersection strategy (IR56d^GAL4/+; UAS-GCaMP6; GR64f-LexA > LexAop-GAL80) and measured activity to a panel of tastants. In agreement with our previous findings, these neurons were robustly responsive to hexanoic acid (6C), but not by sucrose (Figure 6D–F; Tauber et al., 2017). These neurons also responded to other classes of fatty acids including short- (4C and 5C), medium- (7C and 8C) and long-chain (9C and 10C) (Figure 6D–F). Unlike the posterior projections, which respond similarly to all three classes of fatty acids, the response to short-chain fatty acids was lower in the anterior population. Therefore, it is possible that differential response between the anterior and posterior populations provides a mechanism of discrimination between different classes of fatty acids. However, this alone is insufficient to fully explain discrimination between medium- and long-chain fatty acids. Taken together, these findings support the notion that medium-chain fatty acids are detected through a shared sensory channel, allowing flies to distinguish medium-chain from short- or long-chain, but not between different medium-chain fatty acids.

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Raw imaging data from the anterior, non-GR64f-IR56d-expressing region in IR56d^GAL4 flies.

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Receptors for sweet and bitter taste have been well defined in both flies and mammals (Carleton et al., 2010; Hallem et al., 2006; Scott, 2018), but less is known about detection of fats. Previous studies identified IR56d as a receptor for hexanoic acid and carbonation (Ahn et al., 2017; Sánchez-Alcañiz et al., 2018). Our findings suggest that IR56d is selectively involved in responses to medium-chain fatty acids, including 6C, 7C, and 8C fatty acids, and dispensable for responses to shorter and longer-chain fatty acids. Such receptor specificity for different classes of fatty acids based on chain length has not been documented in other systems. In flies, both sugars and fatty acids evoke activity in neurons that co-express the receptors GR64f and IR56d. The finding that short- and long-chain fatty acids also evoke activity in IR56d-expressing neurons posits that additional fatty acid receptors are present in these neurons. Previously, we and others have found that deletion of Phospholipase C (PLC) signaling selectively impairs fatty acid response while leaving sweet taste intact, raising the possibility that activation of distinct intracellular signaling pathways could serve as a mechanism for discrimination between sucrose and fatty acid (Masek and Keene, 2013; Ahn et al., 2017; Tauber et al., 2017), while another suggests TRPA1 and GR64e are targets of PLC and are generally required for fatty acid sensing (Kim et al., 2018). Determining whether or not short- and long-chain fatty acids also signal through PLC may provide insight into whether signaling mechanisms are shared between different fatty acid receptors expressed in IR56d-expressing neurons.

Our aversive taste memory assay confirmed previous findings that flies can discriminate between sugars and fatty acids (Tauber et al., 2017), and led to the surprising observation that flies can distinguish between different classes of fatty acids, even though the baseline responsiveness to short-, medium-, and long-chain fatty acids was similar in innate preference assays. Fatty acids are natural by-product of yeast fermentation (Diwan and Gupta, 2018; Nyanga et al., 2013; Oliveira et al., 2011), and their abundance in peaches, for example, declines after ripening (Duan et al., 2013). Further, fatty acids have antifungal activity, which scales with chain length (i.e., the greater the chain length, the greater the antifungal efficiency; Pohl et al., 2011). Thus, the ability to discriminate between different classes of fatty acids is likely to be important in determining the stage of fruit ripeness, degree of fermentation, and the general palatability of a potential food source/oviposition site.

The finding that flies can distinguish between different classes of fatty acids contrasts with the results of a previous study that applied a similar assay and found that flies were unable to discriminate between different sugars or bitter compounds (Masek and Scott, 2010). One possibility is that this is due to differences in fatty acid detection, which is dependent on IRs, and sweet and bitter tastant detection, which relies on GRs (Chen and Dahanukar, 2020). Our findings highlight the complexity of taste discrimination, which extends beyond simple PER as a readout for taste. For example, all types of fatty acids tested increase GR64f neural responsiveness; however, only GR64f neurons are required for PER to medium-chain fatty acids, thereby raising the possibility that short-, medium-, and long-chain fatty acid taste discrimination occurs through different neural channels. These findings stress the need to define the fatty acid receptors and neural circuits that govern responses to short- and long-chain fatty acid taste. Furthermore, the ability of the Drosophila the taste system to discriminate suggests it may be more like the olfactory system than previously appreciated. Flies are able to distinguish between many different odorants, likely due to the complexity of olfactory coding at the level of the receptor as well as in the antennal lobe (Amin and Lin, 2019; Cognigni et al., 2018; Guven-Ozkan and Davis, 2014). However, flies can also discriminate between odorants sensed by a single olfactory receptor, suggesting that temporal coding also plays a role in discrimination (DasGupta and Waddell, 2008). It is possible that similar mechanisms underlie discrimination between different classes of fatty acid tastants.

The Drosophila genome encodes 66 IRs, which comprise a recently identified family of receptors implicated in taste, olfaction, and temperature sensation (Benton et al., 2009; Rytz et al., 2013). IRs are involved in the detection of many different tastants and function as heteromers that confer sensory specificity (Rytz et al., 2013; van Giesen and Garrity, 2017). While IR56d expression is restricted to a subset of sweet taste neurons, it likely functions in a complex with IR25a and IR76b, all three of which are required fatty acid taste (Ahn et al., 2017; Sánchez-Alcañiz et al., 2018). Other tastants whose responses are mediated by IRs are also likely to be detected by IR complexes. For example, roles for IR25a, IR62a, and IR76b have been described for Ca²⁺ taste (Lee et al., 2018). The broad degree of co-expression of IRs in the brain and periphery can provide candidates for those involved in detecting short- and long-chain fatty acids.

The identification of taste discrimination between different classes of fatty acids provides the opportunity to identify how different tastants are encoded in the brain and how these circuits are modified with experience. Although projections of primary taste neurons to the SEZ have been mapped in some detail, little is known about connectivity with downstream neurons and whether sensory neurons responsive to different appetitive tastants can activate different downstream circuits. Recent studies have identified a number of interneurons that modify feeding, including IN1, a cholinergic interneuron responsive to sucrose (Yapici et al., 2016), E564 neurons that inhibit feeding (Mann et al., 2013), and Fdg neurons that are required for sucrose-induced feeding (Flood et al., 2013). Future work can investigate whether these and other downstream neurons are shared for fatty acid taste. Previous studies have found that incoming sensory information is selectively modulated within the SEZ in accordance with feeding state (Chu et al., 2014; LeDue et al., 2016). It will be interesting to determine if similar modulation promotes differentiation of sugars and fatty acids, which are sensed by shared GRNs. Large-scale brain imaging has now been applied in flies to measure responsiveness to different tastants (Harris et al., 2015), and a comparison of brain activity patterns elicited by different classes of fatty acids may provide insight into differences in their sensory input and processing.

All experiments in this study tested flies under starved conditions, which is necessary to elicit the PER that is used as a behavioral readout of taste acceptance. However, responses to many tastants and odorants are altered in accordance with feeding state (LeDue et al., 2016; Root et al., 2008). For example, the taste of acetic acid is aversive to fed flies but attractive to starved flies, revealing a hunger-dependent switch (Devineni et al., 2019). Similarly, hexanoic acid evokes activity in both sweet and bitter-sensing taste neurons, and the activity of bitter taste neurons is dependent on different receptors from those involved in the appetitive response (Ahn et al., 2017). Further, hunger enhances activity in sweet taste circuits and suppresses that of bitter taste circuits, providing a mechanism for complex state-dependent modulation of taste response that increase activity of both appetitive and deterrent neurons (Inagaki et al., 2014; LeDue et al., 2016).

The neural circuits that are required for aversive taste memory have been well defined for sugar, yet little is known about how fatty acid taste is conditioned. The pairing of sugar with bitter quinine results in aversive memory to sugar. Optogenetic activation of bitter taste neurons that are activated by quinine, in combination with the presentation of sugar, is sufficient to induce sugar avoidance (Keene and Masek, 2012). Further studies have elucidated that aversive taste memories are dependent on mushroom body neurons that form the gamma and alpha lobes, the PPL1 cluster of dopamine neurons, and alpha lobe output neurons, revealing a circuit regulating taste memory that differs from that controlling appetitive olfactory memory (Kirkhart and Scott, 2015; Masek et al., 2015). It will be interesting to determine whether shared components regulate conditioning to fatty acids or whether distinct mushroom body circuits regulate sweet and fatty acid taste conditioning. Further, examination of the central brain circuits that regulate aversive taste conditioning to different classes of fatty acids will provide insight into how taste discrimination is processed within the brain.

All data generated or analysed during this study are included in the manuscript and supporting files. Source data files have been provided for all figures.

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Author details

1. Elizabeth B Brown

   Department of Biological Sciences, Florida Atlantic University, Jupiter, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0003-0825-8199

2. Kreesha D Shah

   1. Department of Biological Sciences, Florida Atlantic University, Jupiter, United States
   2. Wilkes Honors College, Florida Atlantic University, Jupiter, United States

   Contribution

   Formal analysis, Validation, Investigation, Writing - original draft

   Competing interests

   No competing interests declared

3. Justin Palermo

   Department of Biological Sciences, Florida Atlantic University, Jupiter, United States

   Contribution

   Formal analysis, Validation, Investigation, Visualization, Writing - review and editing

   Competing interests

   No competing interests declared

4. Manali Dey

   Interdepartmental Neuroscience Program, University of California, Riverside, Riverside, United States

   Contribution

   Resources, Formal analysis, Investigation, Writing - original draft, Writing - review and editing

   Competing interests

   No competing interests declared

5. Anupama Dahanukar

   1. Interdepartmental Neuroscience Program, University of California, Riverside, Riverside, United States
   2. Department of Molecular, Cell & Systems Biology, University of California, Riverside, Riverside, United States

   Contribution

   Conceptualization, Formal analysis, Investigation, Visualization, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   anupama.dahanukar@ucr.edu

   Competing interests

   No competing interests declared

6. Alex C Keene

   Department of Biological Sciences, Florida Atlantic University, Jupiter, United States

   Contribution

   Conceptualization, Resources, Supervision, Writing - original draft, Project administration, Writing - review and editing

   For correspondence

   keenea@fau.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-6118-5537

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