The strategy to identify chemicals that may act as toxins in the RD-affected colonies included as a first step the untargeted search of metabolites present in nectar samples from those colonies but not present in nectars from healthy colonies (analyzed by NMR and GCMS analyses). Once different signals were identified in the RD nectars, xanthoxylin was isolated from plant material and targeted searches by GCMS in E. cestri secretions and S. schottiana aerial parts were done. Comparisons among these samples allowed us to detect xanthoxylin as a potential xenobiotic that might cause the larval mortality observed in RD-affected colonies. Finally, a larval feeding assay where larval diet was xanthoxylin enriched allow us to identify xanthoxylin as the potential toxic that causes RD.
NMR of Nectars. The multivariate analyses of the NMR data were performed on matrixes previously normalized by data scaling and data transformation (Table S2). The principal component analysis (PCA) on the different matrixes allowed exploratory analyses of the data. The PCA (PC1 63%, PC2 9%, PC3 5%) of the metabolic fingerprints (matrix 1, all bins considered) from nectar samples in D2O showed that they can be differentiated according with the presence of RD (Fig. S1A). Since sugars account for most of the nectar composition, two other data sets were also analyzed: Matrix 2, with bins corresponding to the shift range of sugars, and Matrix 3, with all other bins. In both cases, results also showed differential clustering of nectars from RD and healthy colonies, suggesting a different composition among nectars. In the case of the matrix corresponding to the data from matrix 2 (bins from the “sugar region”) the variance was accounted as follows: PCI, 34 %; PC2, 18% and PC3, 11% (Fig. S1B). For matrix 3 (all data but the “sugar region”) the variance was well explained by 2 components (PC1 80%, PC2 5%; Fig. S1C). Models from Partial Least Squares - Discriminant Analysis (PLS-DA) were then built for the three matrices (Fig. S1D-F). In all cases, the models passed permutation test (R2, Q2 and p values are shown in Table S2). The differences between both nectars was expected as the origin of the nectar raw material impacts on nectar composition (Kortesniemi et al. 2016). Besides, the variability among samples from RD colonies was always lower than among samples from healthy colonies (Fig. S1), a fact that was also evidenced by the results of random forest analyses run on these data (Table 1). Random forest ability to predict the nectar type was always higher for RD samples than for healthy ones, probably correlating to a higher variability in nectars from healthy colonies (Kortesniemi et al. 2016; Schievano et al. 2012; Simova et al. 2012). Since healthy colony samples came from several different locations, with surely different floral offerings, these honeybees would be in contact with more diverse floral resources which could explain the higher variation observed. On the other hand, samples from RD-affected colonies came from fewer locations (see Supplementary material Table S1). These results also suggest the presence of differential compounds in nectars from colonies with and without RD. From the models built, 43 bins with a Variable Importance in Projection (VIP) greater than 2 were identified (Chong et al. 2019). Among these 43 bins, 24 corresponded to the “sugar region” (3.5–5.5 ppm), which would indicate a different sugar composition in nectars from colonies with and without RD (even though we cannot rule out the presence of other compounds with chemical shifts in this region). Indeed, a different sugar composition on honeys of different origins has widely been well documented (Kortesniemi et al. 2016; Schievano et al. 2012; Simova et al. 2012) and t is consistent with what is described in the FAO standards on chemical differences between honeydew and honeys (CX 12-1981 2019). Bins with high VIP in the PLSDA of matrix 3 (shifts from compounds other than sugars) were also detected. Among these bins, the ones present in higher amounts in nectars from RD-affected colonies included chemical shifts corresponding to the aromatic region and around the 3-ppm region. Overall, these results indicate a differential composition of nectars from both kinds of colonies not only related to the saccharide composition but also to other kind of metabolites, allowing to distinguish between nectars from healthy and RD-affected colonies by 1H NMR untargeted metabolomics. However, the great complexity of the matrixes, and the fact that metabolites other than saccharides and aminoacids are in much lower amounts make the identification hard. For that reason, we focus our efforts on the extracts analyzed by GCMS.
Table 1
Random Forest Classification Performance for the Three Data set Analyzed (calculation were done using the Metaboanalyst platform (Xia and Wishart 2016).
|
Healthy
|
RD
|
Classification error
|
Classification error (out of bag)
|
|
Matrix 1 (All bins)
|
Healthy
|
14
|
4
|
0.22
|
0.139
|
RD
|
1
|
17
|
0.06
|
|
|
Matrix 2 (“sugar region”)
|
Healthy
|
16
|
2
|
0.11
|
0.056
|
RD
|
0
|
18
|
0
|
|
|
Matrix 3 (“no sugar”)
|
Healthy
|
13
|
3
|
0.19
|
0.118
|
RD
|
1
|
17
|
0.06
|
|
GCMS of Nectar Extracts. The matrixes from the Paradise-processed GCMS data were subjected to principal component analysis (PCA) to visualize the differences between the healthy and RD nectars. Only in the case of the hexane extracts a clear separation of the chemical profiles of RD colonies compared to healthy ones could be observed (Fig. S2). Further, PLS-DA on data form DCM extracts did not validate (p = 0.86–860/1000). The PCA (singular value decomposition) on the identified peaks from hexane extracts showed that the data was well explained by 2 components (Component 1: 57.7%; Component 2: 25.9%, Fig. S2A) and the peaks that better explained the variance in the data (higher loadings) were at retention times of 17.2, 21.8 and 22.1 min. A partial least squares-discriminant analysis (PLS-DA, Fig. 1) was then used to model the differences between both kinds of samples. Permutation tests based on separation distance were applied to evaluate the reliability of the model (2000 permutations, p = 0.053, Fig. 1B). Overall, the PLS-DA model was found to be a good model for discrimination between both nectars. The validated model had one component, with R2 = 0.69, Q2 = 0.46 and accuracy of 0.83). The 3 most important peaks identified by the VIP scores were at the same retention times already identified by the PCA (17.2, 21.8 and 22.1 min, Fig. 1C). These discriminating metabolites (Fig. 1D-F) were then tentatively identified at the level of compound class from mass spectra acquired during the GCMS analyses (at the identified retention time). The peaks at 17.2 (retention index 1410) and 21.8 (retention index 1650) were classified as sesquiterpenes by their mass spectra (Fig. S3). The compound eluting at 22.1 min had a characteristic mass spectrum [181 (100), 196 (31), 166 (12), 95 (11), 138 (10), 182 (9), 69 (9), 42 (8), 178 (7), 123 (6), 53 (5), 110 (5), 51 (4), 125 (3), 197 (3), 93 (3), 151 (3), 79 (3), 38 (3), 137 (3), 111 (3), 65 (3), 135 (2), 77 (2), 109 (2), 66 (2), 55 (2), 81 (2), 121 (2), 67 (2), 153 (2), 179 (2), 108 (2), 80 (2), 52 (2), 107 (2), Fig. 2A], that exhibited a 93% and 91% similarity with the mas spectra registered for xanthoxylin (1) in the Shim (Adams 2007) and NIST (Linstrom and Mallard 2005) Libraries respectively, and with the mass spectra of a standard of xanthoxylin (Fig. 2B). This spectrum was also like the one from the true standard (Fig. 2B). The retention index calculated for this compound was 1662, similar to the one reported in the Shim Library (1667). Quantification from GCMS data of the corresponding peak show a significant difference between the content in nectars from RD and healthy colonies (p = 0.02, t-test, Fig. 3).
S. schottiana have been reported as a good source of xanthoxylin (Calixto et al. 1990; Lima et al. 1995). Since the other detected metabolites (Fig. 1) were terpene compounds usually found in plants used by honeybees when foraging (Pham-Delegue et al. 1990; Zhang 2018), and also usually found in honeys (Pontes et al. 2007) we focused our efforts on xanthoxylin as the potential toxic substance accounting for the RD effects. To sustain such hypothesis, we explored whether xanthoxylin was in both, excretions from E. cestri feeding on S. schottiania, and the plants themselves (S. schottiania).
Xanthoxylin Detection in Plant Material by TIC and in E. cestri by SIM. The GCMS profiles from total ion chromatograms (TIC) of extracts from plant material and E. cestri honeydew excretions were compared to the profiles from nectars collected from RD-affected and healthy colonies (Fig. 4). The xanthoxylin previously found in extracts from RD-affected colonies (Fig. 1–3) was also detected in plant material at 22.1 min (Fig. 4). When comparing the spectra of the peak at this retention time in the plant material extract, the same characteristic spectrum as in the case of samples from RD-affected colonies was found in both samples (Fig. 2C). However, in the case of the extract of E. cestri secretions, the amount of the sample precluded a conclusive matching. To confirm the presence of xanthoxylin in E. cestri honeydew excretions, the samples were analyzed by SIM GCMS choosing ions 181 and 196 (Fig. 2) to be monitored (Fig. 5). Such analyses allowed for the detection of a peak at the same retention time as xanthoxylin with m/z fragments 181 and 196 in E. cestri samples as well as nectars from RD-affected colonies, but not present in honeys form healthy colonies (Fig. 5).
Xanthoxylin Characterization. To confirm its chemical structure, the targeted compound was purified from the plant extracts (Calixto et al. 1990). Xanthoxylin (C10H12O4, 2'-Hydroxy-4',6'-dimethoxyacetophenone, 1) was isolated as a crystalline white powder; 1H NMR (400 MHz, CDCl3, Fig. S4) δ 14.06 (b, 1H); 6.08 (d, 1H, J = 2.4); 5.94 (d, 1H, J = 2.4);3.87 (s, 3H), 3.84 (s, 3H); 2.63 (s, 3H). 13C NMR (101 MHz, CDCl3) δ 203.17 (C1), 167.60 (C4´), 166.09 (6´), 162.91 (C2´), 106.02 (C1´), 93.48 (C5´), 90.75 (C3´), 55.55 (broad peak for both OMe), 32.92 (C2).The recorded spectroscopic data agreed with the previously reported (Calixto et al. 1990) and also were compared to the one obtained from a true standard (Sigma-Aldrich, 630586-5G, Lot # MKBX3506V). The compound was then identified as 2′-Hydroxy-4′,6′-dimethoxyacetophenone -xanthoxylin- (1). The MS spectrum was as described above.
Larva Bioassay. Once we had detected xantholxylin in the different biological samples (plant material, E. cestri and nectars from RD-affected colonies), we performed a bioassay where larvae were fed on xanthoxylin-enriched diets to mimic the effects of RD. Artificial diet normally used for larval rearing was modified to include nectar from healthy or RD colonies, or nectar from healthy colonies supplemented with xantholxylin. Finally, one group of larvae just received normal artificial diet.
Results indicated that the modification of the artificial diet to include nectar from healthy colonies did not affect larval survival (Log-Rank test: p > 0.05). On the other side, feeding larvae with nectar from RD colonies, or healthy nectar with xantholxylin at 0.2 and 0.4 % (XN_02 and XN_04 respectively), significantly reduced their survival compared with larvae fed on healthy nectar or the artificial diet (Log-Rank test: P < 0.0001 in all cases, Fig. 6). Larvae fed on XN_04 showed a similar survival curve than those fed on RD nectar (Log-Rank test: p > 0.05). In our previous work, we observed that the mortality of larvae fed with nectars from RD-affected colonies and E. cestri secretion was similar or lower than in these cases (Invernizzi et al. 2018). A mortality of more than 60 % at day 4 was observed in the groups fede with xanthoxylin (XN_02 and XN_04) and with nectar from RD-affected colonies. Therefore, we postulate that xanthoxylin may be involved in larval absence within the colonies, one of the main symptoms of RD syndrome.
Final considerations. In a recent study, Invernizzi et al. (2018) reported clear evidence that the massive death of one-day-old larvae with the main symptom of the RD syndrome was associated with the collection by foragers of the secretions of E. cestri feeding on S. schottiana trees. However, in that report the compounds involved in larval poisoning remained unidentified. In the present study, we show the first results of the chemical analyses and profile comparisons of nectars from healthy and RD-affected colonies. 1H NMR spectra of nectars from RD-affected colonies show several different signals than the spectra of nectars from healthy colonies. Some of these signals are indeed due to differences in the composition in carbohydrates and aminoacids, and future elucidation will allow us to chemical characterized these nectars. By GCMS we were able to show that nectars from diseased colonies share xanthoxylin (a metabolite which is absent in nectars from healthy colonies) with the extracts from S. schottiana and the secretion of planthoppers feeding on S. schottiana. As mentioned, xanthoxylin had been already reported from S. schottiana trees (Calixto et al. 1990). Thus, this compound was identified as the probable causal agent of the larval death, which was confirmed in the tests carried out feeding larvae in the laboratory.
As honeybees have been observed foraging on E. cestri secretions, our results suggest a pathway where S. schottiana trees produce xanthoxylin that is ingested by E. cestri. Then, E. cestri, in the process of filtration of the ingested sap to concentrate aminoacids, produce xanthoxylin rich secretions upon which bees forage. In this way, bees bring xanthoxylin to the colony that is incorporated in the nectar fed to 1st instar larvae which, as it was shown in the bioassay, died because of its ingestion. Xanthoxylin, first isolated from Xanthoxylum alatum (Rutaceae), has also been reported in different species belonging to the families Euphorbiaceae, Piperaceae, Apiaceae, Rutaceae, etc. (Chermenskaya et al. 2012). In relation to other biological activities, xanthoxylin has been previously reported as an antagonist of contractions of smooth and cardiac muscles of vertebrate in vitro (Calixto et al. 1990; Cechinel et al. 1995), and also exhibits activity against some bacteria of the urinary tract (De Godoy et al. 1991) and some fungus (Lima et al. 1995; Pinheiro et al. 1999). Indeed the antifungal activity of xanthoxylin supports the popular use of plant extracts containing this compound (Lima et al. 1995). Besides, there are only a few reports regarding anti-insect effects of xantholxylin containing extracts: it has been identified as the major constituent of active fractions from extracts of Ungernia severtzovii (Amaryllidaceae) that exhibited anti-aphid activity (Chermenskaya et al. 2012); and extracts of Zanthoxylum bungeanum (Rutaceae) that had deterrent effects on oviposition and feeding of Sitotroga cerealella (Lepidoptera: Gelechiidae) (Ge and Weston 1995). Our report here shows that xanthoxylin is also toxic to honeybee larvae. Even though we were able to mimic the RD effects on 1st instar larvae, when feeding them with xanthoxylin-reach diets, we cannot rule out that other compounds from the diet could also contribute to the toxicity of nectars in RD-affected colonies. Indeed, other compounds (8-hydroxyquinoline derivatives) with insecticidal properties have been reported in other Sebastiania species (Lee et al. 2010).
Honeybees can avoid collecting nectars that contain toxic substances from the plants due to a learning process where the honeybees associate a particular nectar with a toxic effect (Wright et al. 2010). However, they do not avoid collecting E. cestri secretions with toxic substances from S. schottiana. This apparent contradiction may arise from the fact that these toxic substances do not affect the adult honeybees, precluding them from establishing this association. Likewise, it is unlikely that adult honeybees, which obtain food from several plants, are capable to associate a carbohydrate source with a larval intoxication within the colony. Nor can it be ruled out that honeybees, a generalist species that have few gustatory receptors, do not detect the low concentrations of xanthoxylin that are present in E. cestri secretions (Robertson and Wanner 2006).
Future work should focus on how xanthoxylin affects the physiology, morphology, and development of the larvae, as well as whether xanthoxylin has also an effect on apoptosis as it was already found for the ingestion of RD honeydew (Viotti et al. 2021). Besides, it would be interesting to know whether xanthoxylin is stable or breaks down over time in the nectars, as it does in aqueous solution (Kwon et al. 2014), changing in this way its toxicity overtime.
To our knowledge, this is the first report not only of a xenobiotic present in the secretions of a planthopper that can emulate the RD syndrome in 1st -instar honeybee larvae, but also, we here showed evidence of an interspecific flow of xanthoxylin among three trophic levels that has relevant consequences on the survival of the honeybee colonies.