1 INTRODUCTION

Aquatic ecosystems in recent decades are increasingly affected by various contaminants with the increase in anthropogenic activities. Hepatotoxic microcystins (MCs), produced by Microcystis, are common contaminants in water bodies because of the occurrence of cyanobacterial bloom (Huisman et al., 2018). These toxins may not only result in the poisoning and death of aquatic animals (Stewart et al., 2008) but may also threaten human health by accumulating through the food chain (Chen et al., 2009).

The accumulated MCs are potent inhibitors of protein phosphatases 1 (PP-1) and 2A (PP-2A) and cause cellular oxidative stress through the formation of reactive oxygen species (ROS) (Amado and Monserrat, 2010). As a multipathway process, the biological responses to MC toxicity are often reflected in the optimization of gene transcription, protein expression, and metabolite profiles (Campos and Vasconcelos, 2010). While transcriptomics and proteomics are used to predict what will happen, metabolomics can state what is actually happening. Metabolomics relies on the detection of small endogenous metabolites (molecular mass 50–2 000 Da) in different biological samples (fluids, cells, tissues, organs, and organisms) (Viant, 2007).These metabolites include not only primary metabolites (sugars, amino acids) that are essential for various biological functions of a living organism (e.g., growth, reproduction), but also specialized metabolites (e.g. alkaloids, flavonoids) that are involved in the interactions between organisms and their environment (Hani et al., 2021). It is also a rapid and cost-effective analytical technique that detects relative changes in the spectral pattern of a tissue/organ or even whole tissue extract (Tikunov et al., 2010). Therefore, it is well suited to reflect biological effects of known and unknown environmental stressors on organisms. The applications of this technique to unveil the modes of action of environmental stressors and to identify possible biomarkers in ecotoxicology have been reported in a recent, detailed, and comprehensive review covering nuclear magnetic resonance (NMR)-based metabolomics research conducted to date on aquatic organisms (Cappello, 2020).

At present, only a few studies have reported about the metabolic responses to MC, which consider the human cell line (Birungi and Li, 2011), the liver and urine of rats (He et al., 2012; Cantor et al., 2013), and the liver or whole body tissues of fish (Sotton et al., 2017; Yoon et al., 2017), by using omic approach. These studies have discovered many potential biomarkers and demonstrated the significant value of metabolomics in elucidating the toxicity of MC. However, there were differences in the interaction of vertebrates and invertebrates with MC-producing cyanobacteria and MCs (Wiegand and Pflugmacher, 2005). Some invertebrates, such as molluscs, not only may accumulate higher levels of MCs than vertebrates (Martins and Vasconcelos, 2009), but also can effectively remove them from tissues (Bownik, 2016). Even more remarkable is that gastropods seem to exhibit greater MC tolerance than bivalve, which may not survive the cyanobacterial bloom as well as former (Gérard et al., 2009). These facts indicate the possibility that gastropods have some physiological mechanisms that are able to mitigate the effects of bloom-forming cyanobacteria and their toxins.

As a vital primary consumer that is frequently exposed to toxic cyanobacteria (Qiu et al., 2017), freshwater gastropod is of great importance in human consumption (Yang et al., 2021) and aquatic ecosystem health (Gérard and Lance, 2019). Considering their wide distribution, high abundance, relatively low mobility, suitable size, and their ability to facilitate survey sampling and species identification, gastropods are considered ideal bioindicators of contaminants (Strong et al., 2008; Amorim et al., 2019). Therefore, interactions between gastropods and cyanobacteria have elicited attention (Bownik, 2016). At present, a wealth of information about the response of freshwater gastropod to toxic cyanobacteria, that is, from toxicokinetics to phenotypic trait, including histopathological, biochemical, and ecological effects, is available (e.g. Zhu et al., 2011; Zhang et al., 2012, 2016; Lance et al., 2016; Qiu et al., 2017). However, the physiological and biochemical mechanisms of the regulation of the defense responses to MC observed in gastropods are still unclear.

Hepatopancreas of the freshwater snail is not only the crucial site of xenobiotic metabolism and detoxication, but also primary target organ for MCs accumulation (He et al., 2012; Pham and Utsumi, 2018). Foot muscle of the snail is the main edible part for human food consumption (Yang et al., 2021). Our investigation focusing on the tissues mentioned above can reveal the toxic effects of MCs on metabolic phenotypes of gastropod and identify novel hepatotoxic biomarkers for better understanding of the underlying detoxication mechanism to resist MCs intoxication. The results and NMR-based metabolomic analyses will provide novel insights into the defense mechanisms of MCs and food nutrition and safety issues at the molecular level in the freshwater snail.

2 MATERIAL AND METHOD 2.1 Biological material

Bellamya aeruginosa individuals were collected by hand picking from the littoral zone of water body (Yinzhou Wetland Park, 29.81°N, 121.53°E) with no cyanobacterial bloom record (Supplementary Fig.S1). The water quality parameters of wetland met the requirements of type III in the National Water Quality Standard for Surface Waters in China (GB3838-2002). To avoid background noise due to gender differences in the separation of different treated individuals, only immature female individuals (ca. 12–15-mm shell length) were identified for the experiment based on the growth reference data of B. aeruginosa (Chen, 1987). Gender was determined after being brought back to the laboratory based on the shape of the right tentacle (Lei et al., 2017). The snails were acclimatized under constant room temperature and natural irradiance and fed with Scenedesmus quadricauda for one week before the experiment. The green alga S. quadricauda was provided by the Aquatic Ecology Laboratory of Ningbo University and maintained in NMB3 medium (KNO₃ 100 mg/L, KH₂PO₄ 10 mg/L, Fe-citrate·5H₂O 3 mg/L, VB₁ 6 μg/L, VB₁₂ 0.05 μg/L) under constant room temperature and natural irradiance. Microcystis aeruginosa FACHB-905 is a MC-producing strain, produces microcystin-LR about 0.61 μg per 10⁷ viable cells (Sun et al., 2012), while the M. aeruginosa FACHB-469 is a non MC-producing strain, without MC biosynthesis (mcy) gene cluster (Zou et al., 2018). The both strains of M. aeruginosa were obtained from the Institute of Hydrobiology, Chinese Academy of Science. M. aeruginosa was cultivated in BG-11 medium at 25 ℃ under 36 μE/(m²·s) illumination with a 14-h: 10-h light/dark cycle.

2.2 Experimental setup

An exposure experiment to lasting fortnight was conducted in 24-L aquariums under constant room temperature and natural irradiance. The snails (mean wet weight 0.817±0.169 g) were exposed to MC-producing M. aeruginosa FACHB-905 (toxic group for short) and non MC-producing M. aeruginosa FACHB-469 (non-toxic group for short), respectively. Eight glass containers (as eight replicates) were assigned for each treatment. 20 L of algal suspension was assigned to ten snails in an aquarium. The algal density of M. aeruginosa was set as 3 mg C/L, which was close to the lower value observed during cyanobacterial bloom (Shi et al., 2018). The algal suspension was restocked every day. At designated exposure time (Days 1, 7, and 14), three snails in each aquarium were dissected for metabolomics studies on intact tissues, metabolomics studies on tissue extracts and MC content analysis, respectively.

2.3 Sample preparation for NMR spectroscopy

After rinsing with saline in deuterated water and quenching with liquid nitrogen, intact hepatopancreas tissue samples (10–15 mg) were packed into 4-mm zirconia rotors for high-resolution magic angle spinning nuclear magnetic resonance (HR-MAS NMR) analysis (Zhang et al., 2011).

The extraction of aqueous metabolites was conducted as previously described in Li et al. (2019) with minor modifications as follows: frozen hepatopancreas (ca. 60 mg) or muscle (ca. 150 mg) tissue was homogenized and ultrasonicated in ice bath after adding 600 μL of acetonitrile with Na-K phosphate buffer (acetonitrile: buffer=1:1, 0.1 mol/L, 0.1% sodium azide and pH 7.4). Subsequently, the samples were centrifuged at 12 000 r/min for 10 min at 4 ℃, and the supernatants were collected. This step was repeated twice, and the supernatants were freeze-dried after the evaporation of acetonitrile in vacuo. Each aqueous phase tissue extracts was dissolved again separately in 600 μL of 0.1-mol/L deuterated phosphate buffer (0.005% 3-(trimethylsilyl)-1-propanesulfonic acid sodium salt (TSP) and 0.1% sodium azide). After further centrifugation, 550 μL of the supernatant of each sample was placed into the 5-mm standard NMR tube for analysis.

2.4 ¹H NMR acquisition

¹H NMR profile of aqueous tissue extracts were acquired at 300 K on a Bruker AVANCE III 600-MHz spectrometer (operating at 600.13 MHz for ¹H) equipped with a Bruker inverse cryogenic probe, whereas ¹H HR-MAS NMR spectra of intact hepatopancreas tissue were recorded at 283 K on a Varian INOVA-600 spectrometer with a Varian Nanoprobe and spinning rate of 2.5 kHz because of hardware restriction. For aqueous hepatopancreas extracts, 1D ¹H NMR spectrum was recorded using the first increment of NOESY pulse sequence (recycle delay-90°-t₁-90°-t_m-90°-acquisition) with recycle delay of 2 s, t₁ of 3 μs and the mixing time, t_m, of 100 ms. All of the ¹H NMR spectra were rectified through a series of processes, including centering at the resonance signal of water, apodization through multiplication with an exponential decay that corresponded to 1-Hz line broadening, Fourier transformation, phase adjustment, baseline correction, and calibration with the methyl singlet of TSP at chemical shift (δ) of 0.00 by using TopSpin 2.0 (Bruker Biospin GmbH, Rheinstetten, Germany). COSY, TOCSY, HSQC, and HMBC spectra of selected samples were acquired and processed for NMR signal assignments, as described previously (Dai et al., 2010).

2.5 NMR spectra data processing and analysis

Regions distorted by imperfect water saturation (δ 4.69–5.14 for intact hepatopancreas tissue, and δ 4.68–5.12 and δ 4.50–5.30 for aqueous hepatopancreas and muscle extracts) were discarded. The spectral region δ 0.7–8.8 was divided into many equal width segments with 1.6 Hz width by using AMIX 3.8.3 (Bruker Biospin GmbH, Rheinstetten, Germany). Each segment (integral region) was normalized to the total sum of all spectral integrals to compensate for the overall concentration differences prior to statistical data analysis.

Principal component analysis (PCA) was then carried out to examine the intrinsic variation within the dataset by using SIMCA-P⁺ 11.0 (Umetrics AB, Umeå, Sweden). Orthogonal Projection to Latent Structure with Discriminant Analysis (O-PLS-DA) was subsequently applied to maximize the separation between the treatments by using NMR data (scaled to unit variance) as X-matrix and class information as Y-matrix. Eightfold crossvalidation and model permutations (200 permutations) were conducted to evaluate the accuracy of O-PLS-DA models (Trygg and Wold, 2002; Eriksson et al., 2006). The quality of the model was described by the parameters R²X, representing the total explained variations, and Q², indicating the model predictability related to its statistical validity. The loadings were plotted after back-transformation with the weight of each bucketed region (Cloarec et al., 2005) using the integrated color-coded correlation coefficients (r) of the metabolites that caused the dissimilarity between treatments in the coefficient plots. The coefficient plots were made by using MATLAB 7.1 (The Math Works Inc., MA, USA) with some modifications. The lower the color temperature (e.g. red), the more significant the capability of the metabolites (positive or negative) is in separating between the treatments. According to the significance testing of the Pearson product-moment correlation, the cutoff of the correlation coefficient is set to 0.666 based on the level of confidence of 95% (n=8) (Xiao et al., 2008).

2.6 Quantification of MCs

Dissected tissues (hepatopancreas and foot muscle) were weighed before and after lyophilization. Microcystin extraction was conducted as previously described in Zhu et al. (2011) with minor modifications as follows: grounded tissues were extracted in 100% methanol. The methanol extract was then mixed with equal volumes of hexane under vigorous shaking. The upper layer was discarded, and the obtained methanolic fraction was passed through pre-conditioned C-18 cartridge (Supelco Inc., Bellefonte, USA) and then eluted with step-gradient of methanol. The methanolic fraction was dried and redissolved in 1.0 mL of the deionized water. This suspension was stored at -20 ℃ for subsequent MCs analyses.

MCs concentrations in tissues was determined by the immunoassay method using an ELISA test kit (sensitivity: 0.1 μg/L), with a detection range of 0.1–2 μg/L microcystin (Beacon Analytical Systems, Portland, ME, USA). All ELISAs were performed according to the manufacturers' instructions. The Beacon Microcystin Plate Kit is not available for the identification microcystin variants. Thus, MCs concentration is expressed as the equivalent of MC-LR.

The recoveries for MCs extraction and matrix effects were determined by spiking different tissues of snails with MC-LR standard (3 μg/g dry weight (DW)) (purity > 98%, MedChemExpress, Monmouth Junction, NJ, USA) (Zhang et al., 2016). The response was compared to 100% methanol spiked with the same amount. The MCs extraction efficiency was 86.2%–91.9% in different tissues. Matrix effects were negligible for the two tissues of the snails (from 0.9% to 8.1% of differences between matrix and methanol results with an average of 3.8%). Due to the high recoveries of MCs extraction and low matrix effects of the assay methods, the MCs contents data in the present study were the actual determined data, without any additional calculation using recoveries and matrix effects.

3 RESULT 3.1 Quantitative analysis of MCs

Table 1 shows the dynamics of MCs concentrations in tissues during the fortnight exposures. No MCs was detected in the hepatopancreas and the muscle in the non-toxic group all the time. By contrast, ELISA analysis showed that amounts of MCs were present in the tissues after 7 d of feeding, thereby reaching as much as 1.29±0.48 μg/g and 0.07±0.02 μg/g in hepatopancreas and muscle, respectively. The highest MCs concentration in the toxic group was observed at day 14. Nonetheless, the MCs concentration in hepatopancreas was significantly higher than that in the muscle (Table 1).

3.2 Metabolite assignment

In this study, 40 metabolites, which included various amino acids, carboxylic acids, nucleotides, choline metabolites, trimethylamine N-oxide (TMAO), betaine, and energy substances, were identified (Supplementary Table S1). The representative ¹H NMR spectra of the muscles in B. aeruginosa are shown in Fig. 1. The spectra of muscle tissues contained signals from amino acids, lactate, choline metabolites, glucose, and nucleotide metabolites, such as 5'-Adenosine monophosphate (5-AMP). No significant metabolomic changes were observed when the NMR profiles of muscle extracts from different treatments were compared.

The representative ¹H NMR spectra of intact hepatopancreas tissue and hepatopancreas extracts in B. aeruginosa are shown in Fig. 2. The ¹H HR-MAS NMR spectra of intact hepatopancreas tissues contained signals from lipid moieties, amino acids, organic acid, choline, phosphocholine (PC), glycerophosphocholine (GPC), TMAO, betaine, and carbohydrates (Fig. 2a & b). In the ¹H NMR spectra of aqueous liver extracts, additional signals, such as threonine, methionine, and aspartate, were obviously observed for polar (hydrophilic) amino acids, expect for those metabolites observed in intact tissues. The visual inspection of the NMR profiles showed that the MC-producing cyanobacteria-treated snail had lower energy substance levels than the non-toxic group snail in hepatopancreas tissues (Fig. 2).

3.3 MC-producing cyanobacteria-induced metabolomic changes

No outliers were observed for all the samples when the PCA of the normalized NMR dataset. O-PLS-DA was carried out to compare the differences between the NMR spectra from the MC-producing cyanobacteria-treated and non-toxic group snails at specific sampling time. The values for R²X and Q² suggest that the six O-PLS-DA models are reliable, and the differences between the two treatments are significant in the ¹H NMR spectra of intact tissues and aqueous extracts (Table 2). The metabolic profiles of the liver extracts were changed considerably after the MC-producing cyanobacteria treatment, as shown in coefficient plot (Fig. 3). Compared with the non-toxic group snails, MC-producing cyanobacteria-exposed snails have significantly lower levels of hepatic lipids, glucose, and glycogen and higher levels of amino acid, 3-HB, lactate, betaine, and membrane related metabolites (choline, choline-O-sulfate, PC, and GPC). Similar to aqueous extracts, significant changes were also found in the metabolic profiles of intact tissues (Fig. 4). Such differences became more pronounced with the increase in choline and its derivatives, acetate, glutathione (GSH), and various amino acids. The decreases in the energy substance in the intact hepatopancreas tissues from MC-producing cyanobacteria-exposed snails were also found.

4 DISCUSSION

MCs contents in the liver increased gradually all the time with the final value of 3.17 μg/g after 14 days of exposure, thereby indicating the significant accumulation of MCs in the hepatopancreas of snail. The MCs concentration in the foot muscles was obviously lower than that in liver. These results are consistent with the previous laboratory study on MCs accumulation in freshwater snails (Zhang et al., 2016). The difference of MCs content among tissues was considered to be due to the higher accumulation of MCs in the hepatopancreas, which is the target organ (Martins and Vasconcelos, 2009; Pham and Utsumi, 2018). This observation may also explain the insignificant metabolic alterations in the foot muscle between treatments.

However, metabolic perturbation of hepatopancreas was aggravated as the level of accumulated MCs raised over time in the MC-producing cyanobacteria treatment. Only a few amino acids, choline, and choline derivatives responded quickly and showed a significant increase at the initial stage of exposure. The decline of energy substances were accompanied by the elevation of various amino acids and carboxylic acids after 7 days of exposure, and the metabolic response was similar in the middle and late stages of exposure, thereby implying that MC-induced hepatic metabolic disruptions are influenced by exposure time.

4.1 Amino acid metabolism

The elevation of glutamate and alanine is usually observed in the hepatopancreases of abalones after their exposure to organic pollutant (Zhou et al., 2010; Lu et al., 2017). Moreover, these elevations might reflect the demand for a large amount of glucoplastic amino acids for energy metabolism in gastropods under stress. The level of GSH, which is the product of glutamate, is also increased in our study. GSH is known to participate to the MC detoxification (Campos and Vasconcelos, 2010) and to the antioxidant response (Amado and Monserrat, 2010) in aquatic organisms. Usually, the response of mollusks to xenobiotics, such as MCs, is the upregulation of GSH synthesis (Sabatini et al., 2011) and the elevation of GSH concentration (Zhang et al., 2016).Thus, the increase of GSH in snail treated with the MC-producing strain could support the activation of antioxidant and detoxification processes in order to cope with the presence of the MC and its deleterious effects in hepatopancreases cells. In addition, MCs exhibited notable elevation in branched chain amino acids (BCAA) in the hepatopancreas, which included leucine, isoleucine, and valine. The increases in these amino acids were relative to the stress in clam (Liu et al., 2013). BCAA also are considered to provide energy and are used as the precursors for the biosynthesis of new protective molecules (Calder, 2006).

4.2 Glucose and glycogen metabolism

The energy expenditure and changes in the saccharometabolism induced by the environmental stress in the snail were similar to those reported during estivation because of feeding cessation (Abou Elseoud et al., 2010). In addition, cyanobacteria are known to have low food quality for freshwater mollusk because of nutritional deficiency (Naddafi et al., 2007). If the lower energy substance level were a response for the poor food quality of cyanobacteria, then snails in non-toxic groups would have the same metabolomic alterations. However, a significant difference between the treatments implied that these metabolic changes might be induced by the MCs rather than by hunger.

The suppression of protein phosphatase by MCs may lead to hyperphosphorylation while activating glycogen phosphorylase and suppressing glycogen synthase; the ultimate net effect of which is glycogen depletion (Guzman and Solter, 2002). MCs are potent and specific inhibitors of glycogen synthase activity in rodent liver cells (Lavoie et al., 1991). In gastropods, such as the B. aeruginosa snail, glycogen is considered the principal energetic reserve. Carbohydrates are the primary and immediate source of energy for snail exposed to stress conditions (Ansaldo et al., 2006). Compared with the non-toxic group, snails exposed to MC-producing Microcystis exhibited significantly reduced hepatic glucose/glycogen levels (Fig. 5). The decline in glycogen content in hepatopancreas indicates its rapid utilization as a consequence of MCs stress. Such depletion in the level of glucose has also been observed in gastropod that responded to pesticides (Tripathi and Singh, 2004), heavy metal (Ansaldo et al., 2006), organic pollutant (Zhou et al., 2010), and parasitic infection (Abou Elseoud et al., 2010). Previous studies have also shown that various enzymes can metabolize glycogen, such as phosphoglycerate kinase, which are up-regulated following M. aeruginosa exposure in the digestive tract of mussel (Martins et al., 2009). A cyanobacterial bloom can promote hypoxia/anoxia, and trigger anaerobic respiration in aquatic animals. Increased phosphoglycerate kinase levels could contribute to higher metabolic energy yield through anaerobic glycolysis (Acevedo et al., 2001). These increases suggest a possibility of a shift from aerobic metabolism toward anaerobic metabolism because of insufficient energy production under tissue hypoxic conditions. Moreover, the genes related to saccharometabolism were up-regulated under MCs stress, for instance, lactate dehydrogenase (LDH) B-type subunit in fish (Cui et al., 2011). In consonance with the up-regulation in LDH genes, increase in the lactate level was observed. These changes suggest the mobilization of various energy pathways to meet higher energy demands for mitigating MCs stress.

4.3 Lipid metabolism and oxidation

An increase in ketone bodies, such as D-3-hydroxybutyrate, was observed in the hepatopancreas from the MC-producing cyanobacteria-treated snails. These compounds are the intermediate products of mitochondrial fatty acid β-oxidation, and their increase seems to indicate that MCs exposure might enhance fatty acid oxidation (Fig. 5). However, the previous investigation found that MCs strikingly inhibited the abundances of enzyme related to fatty acid β-oxidation in the hepatic tissue of zebrafish (Wang et al., 2010). This conflict may be related to the differential expression of a bound protein associated with fatty acid metabolism between vertebrate and invertebrate (Haunerland and Spener, 2003).

In addition, MCs exposure significantly increased the level of acetate, which is considered the final product during peroxisomal fatty acid oxidation in liver cells (Leighton et al., 1989). The oxidation of lipids often results in the generation of hydrogen peroxides, which in turn causes oxidative damage by free radical. Oxidative stress and tissue damage in the liver have been widely observed after the exposure of MC-producing cyanobacteria; and the generation of ROS is assumed deeply involved in the principal mechanism of MC toxicity (Amado and Monserrat, 2010). Oxidative stress eventually led to a series of antioxidative responses in organism. An increase in glutathione levels was found in the snail hepatopancreas exposed to MCs. Such finding is in agreement with the anti-oxidative processes stimulated by MCs (Sotton et al., 2017). Previous supportive evidence came from MC-induced increase in the activity of glutathione-S-transferase (GST) in gastropods (Zhu et al., 2011) and the up-regulation of the gene expressions for GST sigma class in mussels (Yang et al., 2012).

4.4 Choline and other metabolites

Choline is not only considered as the basic component and essential nutrient of lecithin, but also plays an important role in lipid metabolism. Previous studies have observed a decrease in choline levels in hepatocytes after MCs exposure (Birungi and Li, 2011; He et al., 2012), which suggested an occurrence of choline variation and the disorder of choline metabolism. In the current study, however, the increase in both choline and choline derivatives and decrease of lipid were found. Lipid droplet deficiency has been observed to be coincidentally related to hepatic pathological lesions in the liver of snail exposed to MC-producing cyanobacteria (Zhu et al., 2011). Snail responded to MCs stress by accelerating the catabolism of lipid rather than disrupting choline metabolism.

Another interesting result is an elevated level of betaine, which would be synthesized during choline oxidation; the elevation of betaine is also presumed to be a result of the formation and reactivity of ROS (Kanbak et al., 2001). An increase in creatine is also notable after MC-producing cyanobacteria exposure. Creatine was presumably synthesized in the recruitment of cysteine, which was used to produce protein, glutathione, and taurine subsequently (Clayton et al., 2003). Therefore, the elevation of creatine is a further indication of ongoing tissue recovery. Time-dependent increases in betaine and creatine were also reported after partial hepatectomy, which could support the explanation that these indicators underline the recovery initiation (Bollard et al., 2010). Similar alterations were also reported in previous investigation under MC exposure (Cantor et al., 2013).

5 CONCLUSION

In summary, the present study reveals that the accumulation of MCs could cause metabolomic responses in the hepatopancreas of freshwater snail exposed to MC-producing Microcystis aeruginosa. These metabolome alterations are mainly related to energy expenditure accompanied with various metabolic disorders that involve lipid metabolism, protein catabolism, osmoregulation, glycolysis, glycogenolysis, and TCA cycle. NMR-based metabolomics approach appears to be a useful tool for discovering biomarkers in organisms under environmental stress, such as MC-producing cyanobacteria bloom. Nonetheless, further studies concerning the metabolic response of other tissues are still needed to understand how various tissues work together to ensure the detoxification and survival of Bellamya. In addition, the multi-omics approach combined with transcriptome, proteome, and microbiome is also a promising direction to reveal the defense mechanism from a holistic view.

6 DATA AVAILABILITY STATEMENT

All data generated and/or analyzed during this work are available from the corresponding author on reasonable request.

Electronic supplementary material

Supplementary material (Supplementary Fig.S1 and Table S1) is available in the online version of this article at https://doi.org/10.1007/s00343-021-0336-2.