What Goes in Must Come Out? The Metabolic Profile of Plants and Caterpillars, Frass, And Adults of Asota (Erebidae: Aganainae) Feeding on Ficus (Moraceae) in New Guinea

Insect herbivores have evolved a broad spectrum of adaptations in response to the diversity of chemical defences employed by plants. Here we focus on two species of New Guinean Asota and determine how these specialist moths deal with the leaf alkaloids of their fig (Ficus) hosts. As each focal Asota species is restricted to one of three chemically distinct species of Ficus, we also test whether these specialized interactions lead to similar alkaloid profiles in both Asota species. We reared Asota caterpillars on their respective Ficus hosts in natural conditions and analyzed the alkaloid profiles of leaf, frass, caterpillar, and adult moth samples using UHPLC–MS/MS analyses. We identified 43 alkaloids in our samples. Leaf alkaloids showed various fates. Some were excreted in frass or found in caterpillars and adult moths. We also found two apparently novel indole alkaloids—likely synthesized de novo by the moths or their microbiota—in both caterpillar and adult tissue but not in leaves or frass. Overall, alkaloids unique or largely restricted to insect tissue were shared across moth species despite feeding on different hosts. This indicates that a limited number of plant compounds have a direct ecological function that is conserved among the studied species. Our results provide evidence for the importance of phytochemistry and metabolic strategies in the formation of plant–insect interactions and food webs in general. Furthermore, we provide a new potential example of insects acquiring chemicals for their benefit in an ecologically relevant insect genus.


Introduction
To this day, more than 200,000 specialized plant metabolites have been described, many of which have known or assumed anti-herbivore functions (Kessler and Kalske 2018). In response to this diversity of plant chemical defences, herbivorous insects have evolved various physiological adaptations to circumvent or exploit the specialized metabolites produced by their host plants (Petschenka and Agrawal 2016;Dussourd 2017).
Adaptations to plant chemical defences by herbivores can be specific to a restricted set of compounds in a given class (Lindigkeit et al. 1997), and are typically conserved among closely related herbivore species (Nallu et al. 2018;Allio et al. 2021). Plant chemistry thus often predicts interactions among plants and their specialized herbivores. In some cases, it can be a better predictor of host-use that the relatedness and phylogeny of the host plants (Becerra 1997;Endara et al. 2017). Nymphalid Melitaeii butterflies, for instance, Alyssa M. Fontanilla and Gibson Aubona are Joint first authors. are chemical specialists that can exploit distantly related but chemically similar plants containing iridoid glycosides (Wahlberg 2001). In turn, host plant chemistry can predict host-use by herbivores among both distantly or closely related plants even in extremely diverse systems, such as tropical forests that harbour myriad insect herbivores and plants. For example, polyphenol oxidative activity in leaves of 88 plant species could predict their use by geometrid moths in hyper-diverse food webs in tropical lowland forests in New Guinea (Segar et al. 2017). Such trends occur even among congeneric hosts, with high elevation populations of minimized costs to the insect (Cogni et al. 2012;Zaspel et al. 2014) and the need to study multiple life stages. The tribe Lithosinii is also intimately connected to its lichen hosts from which it sequesters phenolic compounds (Scott Chialvo et al. 2018). Furthermore, Anderson et al. (2017) found that Crambidia cephalica had a distinct metabolomic profile from its Physcia host despite sequestering lichen secondary metabolites. Furthermore, they observed differences across C. cephalica life stages, with the larval and pupal stages having the highest chemical similarity. This body of results highlights how metabolomic approaches can be applied to gain a deeper understanding of host preference and chemistry-based adaptations in insects, especially when sampling across tissue types and life stages.
Here we explore the metabolomes of New Guinean species of Asota (Erebidae: Aganainae), an aposematic moth genus closely related to arctiine moths (Zahiri et al. 2012). Unlike the Arctiinae, Asota and their chemistry have been surprisingly understudied despite being associated with severe skin irritation and fever outbreaks in humans (Wills et al. 2016). The toxicity of caterpillar and adult Asota fluids as well as that of adult scales (Sourakov and Emmel 2001;Wills et al. 2016) are strongly indicative of a physiological adaptation to host plant metabolites. Widescale sampling of lowland and highland food webs in New Guinea revealed that Asota is a Ficus specialist ( Fig. S1) feeding in larger numbers on Ficus species with high alkaloid content and diversity (Novotny et al. 2010;Volf et al. 2018). We use the Ficus-Asota system to quantify alkaloids from the leaves, frass, caterpillars, and adult moths to determine their fates and therefore possible ecological functions. We expect sequestration of the alkaloids in the aposematic caterpillars and adults. Furthermore, given the conservatism in adaptations to host plant chemical defences among closely related herbivores, we expect convergence of alkaloid profiles as modified by the insects between Asota species feeding on different host plants. Through the use of a metabolomic approach, we connect the alkaloids found in Ficus and Asota to see whether the maxim "you are what you eat" applies also to caterpillars.

Study System
We studied two species of Asota (A. eusemioides and A. heliconia) across three species of Ficus (F. septica, F. pachyrrhachis, and F. hispidioides). Because of the complexity of the taxonomy of Asota (Holloway 2022), we became aware that A. heliconia was in fact a duplex of two cryptic species that are partially overlapping across the wide range of what was originally considered one species (Holloway 1988, Supplementary Information). However, these two species show segregation with altitude in New Guinea. This enabled us to establish that we were dealing with only the lowland member of the pair in Madang. A more detailed account is presented in Supporting Information. Our field collections also showed that caterpillars from each of the two Asota species were largely restricted to only one or two Ficus species. We found A. eusemioides only on F. hispidioides and F. pachyrrhachis, while almost all A. heliconia caterpillars collected for our experiment were from F. septica. Only two A. heliconia caterpillars were found on another Ficus species (F. hispidioides); they were excluded from our study.

Field Experiment
We conducted a two-part experiment in Ohu, Madang Province, Papua New Guinea (− 5.140° 145.410° 200 m) from February to April 2018. Because conditions and rearing approach were consistent across the entire study period, we combined experimental data from the first and second parts for analysis so that four individual trees from each Ficus species were involved (n = 12). While a larger host sample size would have been preferable, replication across insects on the same host plant individual is required in our study. Metabolic analysis of resource and herbivores can only establish compound fate if all resource compounds have equal possibility to be found further down the trophic chain. And as we were mainly interested in how insects vary in their responses to a common resource, maximizing variation at the resource level is not desirable. Moreover, designing complex experiments in remote tropical rainforests are often shaped by logistical limitations. Thus, given our research focus and the resources at hand, we decided to maximize replication at the level of the organism being studied (i.e., the insect) and control for repeated measures at all steps.
Larval Development in Asota The first part of our experiment was aimed at rearing caterpillars on each host to adulthood; this allowed accurate identification of species and developmental stage, and confirmation that body size increased predictably across instars (Dyar 1890). We selected two individual trees from each host species (n = 6) and attempted to rear five individual first instar caterpillars (collected from the appropriate host species in the surrounding forest) to adulthood (n = 30). Individual caterpillars were placed on a single branch of the Ficus species from which they were sampled and enclosed in a fine breathable mesh for rearing (Fig. S2). Larvae were reared on young, fully expanded, and healthy leaves until their last instar, and frass was regularly removed (at least daily) to keep conditions as clean as possible. Caterpillars were followed from 13/02/2018 until 01/03/18, by which time 21 out of 30 larvae had entered pupation. Eleven larvae were reared to adulthood and stored at − 20 °C before being freeze dried. Caterpillar body length was measured to the nearest 0.1 cm on a daily basis. We also collected 10 leaves from a separate branch of the same tree before placing the caterpillars (n = 48; leaves from one tree were excluded and one tree was sampled for eight leaves). These leaves were placed in an ice box and transferred to a − 20 °C freezer before being freeze dried at the Binatang Research Centre.

Chemical Variation Across Sample Types
For the second part of our experiment, we selected an additional two individual trees from each host species, for a total of 12 trees. For each tree, we aimed to place 15 individual caterpillars of the appropriate Asota species on individual branches covered by mesh bags. Due to the local availability of first instar caterpillars, however, we ended up with 29 caterpillars on F. septica, 32 on F. hispidioides, and 31 on F. pachyrrhachis, for a total of 92 caterpillars. As with the first part, caterpillars were allowed to feed only on young and healthy leaves.
Once caterpillars had molted into the last instar, ca. one half (n = 44) were freeze dried and collected as larval samples while the other half (n = 48) were reared to adults. The former were starved for six hours prior to freeze drying to ensure that there was no contamination from plant metabolites. Caterpillars in the rearing treatment were allowed to feed for 24 hr after their final molt before being placed into pots with fresh leaves. Their frass was collected every 45 min for four and a half hours. The caterpillars were then returned to their host plants to pupate naturally, and adult moths were freeze dried after emergence. A total of 17 caterpillars from the rearing treatment died in the last instar and were removed; 15 of the 17 deaths were due to parasitoid attack. We also removed four caterpillars and one adult (and their frass samples) due to possible degradation, to give a total of 70 insect samples.
Our aim was to collect six frass samples per caterpillar, for a total of 30 frass samples per tree. Because some samples were pooled in the chemical analysis due to low mass, we ended up with 170 frass samples instead of 180. In these cases, samples from the same individual-but not across individuals-were pooled. Frass was frozen immediately upon collection, as were the leaves upon which caterpillars had fed, and were later freeze dried. As the leaves on which the caterpillars fed were in generally poor condition and potentially influenced by caterpillar feeding itself, we again collected and freeze dried 10 leaves from a separate branch of the same tree to serve as baseline comparison.
After accounting for excluded specimens, a total of 362 samples were used for subsequent analyses. The number of samples for each tissue type and adult body part are reported in Table 1. All materials were sent to the University of Turku for chemical analyses.

Chemical Analyses
We first grouped our samples based on tissue type (i.e., leaves, frass, caterpillars, and adults). Adult samples were then further dissected based on body parts into three subgroups: i) body (which, for this study, was composed of the head, thorax, and abdomen), ii) wings, and iii) legs and antennae. All samples were ground into fine powder by a ball mill. We macerated 10 mg with 1800 µl methanol overnight in cold room, and then extracted via sonication in a water bath for 30 min, centrifuged at 14,000 rpm for 10 min. Supernatants were decanted to new Eppendorf tubes and the methanol was evaporated in an Eppendorf concentrator. Samples were then dissolved in 1000 µl of 5 mM aq. HCl, filtered through 0.20 µm PTFE filters and pipetted into an UHPLC wellplate prior to the UHPLC-MS/MS analyses.
UHPLC-MS/MS analyses were conducted on an Acquity UPLC system coupled with a DAD detector (Waters Corporation, Milfor, MA, USA) and a hybrid quadrupole-Orbitrap mass detector (Q Exactive™, Thermo Fisher Scientific GMbH, Bremen, Germany) via HESI source (H-ESI II, Thermo Fisher Scientific GmbH, Bremen, Germany). The column was Acquity UPLC BEH Phenyl (30 × 2.1 mm i.d.; 1.7 µm; Waters Corporation, Wexford, Ireland). The mobile phases consisted of acetonitrile (A) and 0.1% formic acid (B). The eluent profile was as follows: 0-0.1 min, 3% A in B (isocratic); 0.1-3.0 min, 3-45% A in B (linear gradient); 3.0-3.1 min; 45-90% A in B (linear gradient), 3.1-4.0 min 90% A in B (isocratic); 4.0-4.1 min; 90-3% A in B (linear gradient), 4.1-4.2 min; 3% A in B (isocratic). The eluent flow rate was 0.65 ml/min and injected volume 5 µl. The mass spectrometer was operated in a positive ionization mode with mass range of m/z 120-1000 and with lock mass. The following parameters were used for the positive ionization: spray voltage set at 3.0 kV, N 2 sheath gas flow rate at 60 arbitrary units, N 2 aux gas flow rate at 20 arbitrary units, capillary temperature 380 °C, and S-lens RF level at 60. Orbitrap resolution for full scan was 70,000 (full MS) with an automatic gain of 3 × 10 6 . Data dependent MS/MSspectra was obtained with a resolution of 17,500.
Post analysis data handling was done using Thermo Xcalibur Qual Browser software (Version 3.0.63, Thermo Fisher Scientific Inc., Waltham, MA, USA), Compound Discoverer 3.1 (Thermo Fisher Scientific Inc., Waltham, MA, USA) and MZmine version 2.53 (Katajamaa et al. 2006;Pluskal et al. 2010) to achieve quantitation of all possible ions (as the extracted ion area / mg dry weight of tissue). Compound Discoverer utilized the following parameters: untargeted metabolomics workflow template with mass tolerance of 5 ppm, intensity threshold of 30%, S/N threshold of 3, minimum peak intensity of 1 × 10 6 , and maximum element count of C × 100, H × 200, Cl × 4, N × 10, Na × 4, O × 100, P × 3, and S × 5. For peak detection the following parameters were used: filter peaks true, maximum peak width of 0.5 min, remove singlets true, minimum # scans per peak 5, and minimum # isotopes 1.
Tentative identification of the detected molecules was based on the use of the GNPS analysis environment and its feature based molecular networking (FBMN) (Horai et al. 2010;Pence and Williams 2010;Wang et al. 2016;Nothias et al. 2020). All UHPLC-MS/MS data files were converted to mzXML format using ProteoWizard MSConvertGUI (version 3.0.19316). LC-MS feature detection and alignment for GNPS were done using the following MZmine methods and parameters:  Alkaloids found to be indicative of sample type (see Statistical Analyses for details on alkaloid selection) were further analyzed by MS/MS to elucidate their structures on the basis of accurate masses of the molecules and fragments, and their corresponding double bond equivalents. Potential alkaloid-like compounds were statistically analyzed and 17 focal compounds were selected for closer manual examination of their molecular ions (based on CCA scores on the first two axes, please see below for more detail), MS/MS -spectra, and corresponding double bond equivalent (DBE) which led to structural characterization of an isoquinoline alkaloid (A5), three pyridoindoles (A9, A16, and A28), four seco-phenantroindolizidines (A17, A22, A24, A35), three seco-phenantroindolizidines (A25, A36, A43), two seco-phenantroindolizidine-N-oxides (A27 and A32), one phenantroindolizidine (A30) and three alkaloid-like compounds (A37, A38, and A41) that we could not classify further.
A17 and A22 shared the molecular formula C 23 H 27 NO 5 with molecular ions at m/z 398.19639 and 398.19640, respectively. These alkaloids were characterized as isomers of dihydroxy-trimethoxy-seco-phenantroindolizidine. MS/ MS-spectra obtained for A17 and A22 had major fragments at m/z 70 matching dihydropyrrole and at m/z 218 matching dimethoxyphenol-dihydropyridine. UV absorption maxima were obtained for 17 at 241, 266, and 343 nm and for 22 at 235 and 269 nm. A24 was characterized as dihydroxy-secophenantroindolizidine with molecular ion at m/z 308.16440 and with molecular formula C 20 H 21 NO 2 . For A24, MS/MSspectra showed major fragments at m/z 188, 186, 70, 107, and 212, bearing similarities with other seco-phenantroindolizidines. A35 had molecular ion at m/z 350.21112 and was characterized as dimethoxy-methyl-seco-phenantroindolizidine with molecular formula C 23 H 27 NO 2 . A27 and A32 had both major MS/MS fragment at m/z 86, characterized as N-hydroxydehydropyrrol, indicating presence of N-oxide moiety in the structure. A27 was characterized as hydroxy-dimethoxyphenyl-methoxyphenylhexahydro-indolizine-4-oxide with a molecular formula C 23 H 27 NO 5 , molecular ion at m/z 398.19605 and UV absorption maxima at 245, 261 and 343 nm. A32 was characterized as dimethoxyphenyl-methyloxoniophenyl-hexahydroindolizine-4-oxide with matching molecular ion at m/z 382.20112 and molecular formula C 23 H 27 NO 4 .

Statistical Analyses
Larval Development in Asota We used linear mixed models, implemented using the R package 'nlme' (Pinheiro et al. 2022), to test how caterpillar body size increased across instars. Body length was the response variable, instar and caterpillar species were the fixed categorical explanatory variables, and individual caterpillar was used as the random explanatory variable to account for multiple measures of the same individual dates as it grew. We also tested the size differences among instars of A. eusemioides across its two hosts (F. hispidioides and F. pachyrrhachis) using similar mixed models, but with host species instead of caterpillar species as the explanatory variable.

Chemical Variation Across Sample Types
Based on shared conditions for collection and rearing, we used the combined data from the first and second parts of the experiment in subsequent analyses. For the purposes of initial data exploration, we first ran a partial Principal Components Analysis (pPCA) to visualize the total variability in chemical composition between different tissue types and body parts. The effect of the individual was removed by conditioning the 'community' matrix on a vector coding for the individual sampled in cases of paired measures. Alkaloid concentration in area per g dry weight (DW) was log transformed. Mean values across individual host or insect were used when multiple samples of the same type were taken from the same individual.
Our experimental design necessitated the collection of frass from insects subsequently reared to adults, causing us to have some paired data points. We ran four analysest to explore and control for this non-independence. We first ran a standard CCA (i) in which the response variable was the same 'community' matrix dataset used in the pPCA, and the explanatory variables were tissue type and host Ficus species. Because A. eusemioides is found on both F. hispidioides and F. pachyrrhachis while A. heliconia is restricted to F. septica, the variable 'insect species' is collinear with 'host species'. Host species provides greater resolution and information content and is preferred for data exploration. An additional CCA (ii) included an extra explanatory variable, a vector called 'individual', was used to group any paired observations (e.g., frass and the insect from which it was collected). Next, we performed pCCA (iii) using the same set of variables from ii), with the effect of the individual removed by conditioning the 'community' matrix on a vector coding for the individual sampled. Finally, to further control for the possible influence of the individual on compound selection, we ran a standard CCA (iv; with the same formulation as above) on a reduced data set in which alternating adult or frass data points were removed when both were recorded from the same individual. For all CCAs model simplification proceeded through stepwise permutation tests (999 permutations) in both directions, and adjusted R 2 was used as the stopping criterion. The significance of explanatory variables were summarised as an ANOVA table. All multivariate analyses were conducted in the R package 'vegan' (Oksanen et al. 2020) which implements the CCA following Legendre and Legendre (2012).
Additionally, sampling multiple body parts from the same adult allowed us to compare uptake of chemicals in the same individual. To control for the effect of individual, we visualized the adult body part dataset by using pCCA and adding a vector that grouped all samples taken from the same individual (as used in pPCA). Model simplification and significance followed that above as used for tissue type.
Differences in compound occurrence across tree species and sample groupings were initially tested using linear mixed models implemented in 'lme4' (Bates et al. 2015). These models were tested for dispersion, outliers, distribution of residuals and zero-inflation using the R package 'DHARMa' (Hartig 2020). Because our dataset comprised many zeros, we included a single zero-inflation parameter applying to all observations using the R package 'glm-mTMB' (Brooks et al. 2017). A Gaussian distribution of errors was appropriate for all models. The response variable, alkaloid concentration (peak area/g DW), was log transformed, and the explanatory variables used for the models depended on which dataset was being used. For the tissue type dataset, we used host tree species and sample type (with adult moths split into each species) as explanatory variables.
For the body part dataset, we used sample type (with adults split into each species) as the explanatory variable. We only split adult moths by species, assigning caterpillars and frass to species would create too many multiple comparisons for meaningful interpretation. We performed Tukey's HSD tests for linear combinations of each explanatory variable using the R package 'multcomp' (Hothorn et al. 2008). As our central question necessitated the use of the same individual across or within developmental stages, we included 'individual' as a random effect to all our mixed models.

Chemical Variation Across Sample Types
The pPCA demonstrated a distinct clustering of sample types, with insect tissue broadly grouping together and frass and leaf samples both forming two distinct clusters (Fig. 1a). Several compounds are associated with specific sample types. The first two principal components explained 61% of the total inertia. Standard CCAs with 'individual' included as an explanatory variable (ii in Methods and Materials: Statistical Analyses) explained an additional 6% of the inertia in comparison to CCAs without the variable individual (i in Methods and Materials: Statistical Analyses), although individual was not included as a significant variable following model selection. Chemical composition varied significantly across sample types (F = 36.294, P = 0.001) and tree species (F = 50.858, P = 0.001) respectively; the two variables together explained 68% of the total inertia. These results were also reflected in both (iii) pCCA ( Fig. 1b; sample type: F = 30.075, P = 0.001; tree species: F = 25.023, P = 0.001; 48% of inertia explained by constrained variables and 27% by conditional variables), and in (iv) a simplified version of the analysis with replicated individuals removed (sample type: F = 23.992, P = 0.001; tree species: F = 40.127, P = 0.001; 68% of the total inertia).
There was a much weaker relationship between chemical composition and body part (Figs. 1c and d), although there was some degree of separation between body, wings and legs and antennae. While 36% of the total inertia was explained by the first two principal components, the constrained variables in the pCCA explained only 5% of the total inertia in the dataset. In contrast, conditional variable contributed 61%. Only body part (F = 5.5796, P = 0.001) was significantly correlated to chemical composition, which was collinear with tree species.
For sample type, we selected 17 alkaloids (hereafter referred to as 'indicator compounds') that showed the highest scores on the first two CCA axes (Table 2).
Zero-inflated linear mixed models showed that all indicator compounds except for A9, A16, A37, and 38 differed significantly in occurrence across tree species (Table 3,  Table S1). Four alkaloids that were either present in small amounts (A28 and A37) or absent in leaf tissue (A9 and A16) were found in high amounts in both A. eusemioides and A. heliconia caterpillars and adults (Fig. 2a,b,c). A37 was also absent in A. eusemioides frass (Fig. 2a,b), while A38 was present in very small amounts in frass regardless of Asota species. A43 was present in leaves and frass but in low frequency in A. eusemioides caterpillars and adults (Table 3). Fewer compounds differed significantly across insect tissue (7/17 compounds between adult A.  (d), samples are classified according to adult body parts (i.e., body, wings, and legs and antennae) and Asota species. Alkaloids (shown in grey text in the biplots) selected for further analyses are listed in Table 2 eusemioides and A. heliconia, with 6/17 and 7/17 for respective comparisons to caterpillars) than between adult and frass samples (A. eusemioides: 11/17; A. heliconia: 11/17) and adult and leaf samples (A. eusemioides: 14/17; A. heliconia: 13/17) (Table S1). Leaf tissue was more distinct from insect tissue than frass, while adults and caterpillars most resembled each other in terms of chemical composition. Three indicator compounds (A27, A32 and  A37) showed trends across body parts (Fig. 1d), but these differences were non-significant (Table S2).

Discussion
Our study demonstrates that specialized Asota moths not only bypass putative Ficus defences but derive new and potentially more potent compounds from them. By identifying alkaloids that possibly shape the interaction between Asota and Ficus plants, we also demonstrate that overall chemical composition in adult insects can converge from contrasting chemical starting points. This suggests that these caterpillars filter, ingest and modify specialized plant metabolites to achieve a specific chemical phenotype. Our results thus imply that plant metabolites differ in their bioactivity, and both plants and insects may screen and seek, respectively, the ones that play the strongest roles in their diverse interactions with other trophic levels (Wetzel and Whitehead 2020). Caterpillar and adult profiles of each moth/host combination were broadly similar, forming one large but coherent cluster in comparison with the two distinct leaf and frass clusters. This pattern occurred despite the distinct host plant chemical profiles, with Ficus septica leaves standing out in particular. Indeed, F. septica has been identified to have largely unique defences also by our previous studies on the evolution of both chemical and physical defences among a broader set of New Guinean Ficus species (Volf et al. 2018). That Asota moths processed the alkaloids from this species and the other hosts studied here in a largely similar way supports our hypothesis of chemical convergence across Asota species, probably due to the conservatism in the metabolism of host plant defences among closely related herbivores (Nallu et al. 2018;Allio et al. 2021).
Additionally, our findings on the convergent alkaloid profiles among Asota species suggest that compounds relevant for moth fitness form a small and distinct subset of those present in Ficus tissue. In this case, it is possible that Asota moths screen for active Ficus leaf compounds that they can potentially use to their own benefit. The properties of these key compounds, possibly anti-fungal or anti-predator, remain to be determined but they likely play a defensive role given the high toxicity of Asota (Wills et al. 2016). There are similar parallels from other insect systems where various related compounds are sequestered to produce a limited number of defensive metabolites. For example, Chrysomela leaf beetles sequester several but not all salicinoids to produce salicylaldehyde as a defence against invertebrate predators (Soetens et al. 1998). Since both Asota species studied here have brightly coloured bodies, perhaps the excretion of alkaloids from within the haemolymph is central to their defence (Sourakov and Emmel 2001). This could be supported by the diverse range of alkaloids found in the bodies of our focal taxa.
One key finding was the occurrence of two indole alkaloids (A9 and A16) in insect tissue despite being totally absent from leaves. As far as we are aware, these compounds have not been previously isolated from insect or plant tissue or synthesized artificially. Metabolism of indoles by insects is known; mirid bugs (Hemiptera: Heteroptera) apparently detoxify or modify indoles to prevent them entering the haemolymph (Hori 1979). Indoles are a class of alkaloids best avoided by invertebrate and vertebrate predators alike, as their effects are deleterious and can extend to behavioural modifications. Indole derivatives, for example, increase mortality (likely through neurotoxic activity) in ants (Costa et al. 2019), which are important predators of caterpillars in tropical forests (Sam et al. 2015). Indoles are also widely employed as signalling molecules and are able to counter viral and bacterial pathogens (Lee et al. 2015). We suggest that the two novel indole compounds found in our study are either modified from other Ficus alkaloids or synthesized de novo, and possibly serve a defensive function in the focal system. Until further exploratory research is conducted, we also consider the possibility of these two indole derivatives being produced by endosymbionts. Indeed, the production of bioactive compounds by symbiotic microbes is not a rare occurrence among insects (Beemelmanns et al. 2016). More detailed examination (e.g., precursor feeding) are needed to confirm the molecular pathways involved, but our study opens up a number of opportunities for mechanistic elucidation by highlighting the importance of these particular indole alkaloids. A large number of alkaloids seem to be passively taken up without differences in occurrence across plant, frass, and insect tissue. In comparison to the alkaloids that differed in concertation between the various Asota samples and leaves, these alkaloids may play less important roles in Ficus-Asota interactions. Our previous studies have shown that various groups of insect herbivores show differential responses to chemical defences in Ficus. While Asota prefers to feed on highly alkaloidal Ficus species, alkaloids structure assemblages of other caterpillar groups in the community (Volf et al. 2018). The alkaloids that were passively taken up by Asota could thus be potentially involved in protecting Ficus trees from other insect herbivores.
In contrast to the above subset of compounds, phenantroindolizidine alkaloids appear to be actively expelled through frass. While the effects of these specific compounds on insects have yet to be established, a phenantroindolizidine alkaloid isolated from Cynanchum komarovii (Asclepiadaceae) was reported to have negative effects on the feeding and growth of Plutella xylostella larvae (Guo et al. 2014). We, therefore, assume that the phenantroindolizidine alkaloids characterized in our study are excreted by Asota caterpillars to avoid harmful metabolic effects. However, the ability to deal with these toxic compounds without large differences in growth rates across caterpillar species may help explain specialized Ficus feeding in the genus Asota. While Asota can tolerate these compounds, most groups of insect herbivore avoid feeding on Ficus (Basset et al. 1997). Presumably, this tolerance of a relatively restricted group of alkaloids trades off with an ability to feed more generally on other chemical classes. Additional studies with increased sampling at the host level are needed to study performance as well as the generality of our findings.
In conclusion, our results provide insights on how physiological adaptations could influence host use in a highly specialized tropical food web. Based on our findings and previous work on their taxonomy and biogeography, Asota are well suited for future chemistry-and evolution-based research on phenotypic plasticity and physiological tradeoffs in Lepidoptera (Fordyce and Nice 2008). There are two major clades in a phylogeny of Asota that include New Guinea species, but A. eusemioides and the A. heliconia duplex fall into just one of these (Holloway 2022, Supplementary Information). Whilst A. eusemioides is restricted to New Guinea and nearby islands, the A. heliconia duplex participates in a presumed complex hybrid system that involves several other species over western China and mainland Southeast Asia. A few widespread species and many more localized ones in the clade also occur between this area of the Asian mainland and Australasia. Ficus biogeography is similarly complex, offering a range of opportunities for expansion of a comparative approach to explore selection in geneflow in Asota and other Ficus-feeding Aganainae. One such example is Ophyx, transferred to Aganainae by Holloway (2022), entirely Australasian and exhibiting a bizarre range of secondary sexual structures for pheromone dispersal in the male (Holloway, 1984). Asota, Ophyx and Ficus would therefore make an excellent system for further studying the evolution of detoxification and other metabolic strategies, as well as a useful comparison to other insect groups as more powerful predictive methods are developed (Braga et al. 2021).