P. deltoides pollen and poplar flocs samples used in this study were collected from March to June 2022 in the Wuhu section of the Yangtze River levee (N31.33, E118.38), different trees with the same height and direction). According to the laws of phenology, 7 days after inflorescence protrudes, pollen in indehiscent anthers is defined as immature pollen; the scattered pollen after dehiscent anthers is defined as mature pollen; 20 days after fruit set, poplar flocs in indehiscent pericarp are defined as immature poplar flocs; poplar flocs in dehiscent pericarp are defined as mature poplar flocs (Figure 1A). Collection of immature pollen: Tree pruner cuts off the branches, collects the anthers, brings them back to the laboratory immediately, uses a sharp knife blade to cut the anthers under a microscope, and picks out the pollen with an anatomical needle. Collection of mature pollen: The sampling belt encloses the inflorescence and shakes it violently to shed the pollen. All samples shall be stored in -80°C refrigerator immediately after purification.

Lab-free quantitative proteomics was performed with reference to previous study (Guo et al., 2021). The main processes were as follows: Weigh the appropriate sample into the mortar, add liquid nitrogen and grind thoroughly. The 800μL extraction buffer [Sucrose 2.4 g, NaCl 0.058 g, EDTA·2Na 0.146 g, DTT 0.02 g, 0.5M Tris-HCl (pH6.8) 2.5 mL, 1.5M Tris-HCl (pH8.8) 2.5mL, add ddH₂O to 10mL, dissolve and mix thoroughly] was added to each sample and the mixtures were added with equal volume of Tris-phenol buffer (6.8M, Solarbio life sciences, Beijing, China) and mixed for 30min at 4°C. Then, the mixtures were centrifuged at 7000g for 10min at 4°C to collect phenol supernatants. The supernatants were added for 5 times the volumes of ammonium acetate-methanol buffer (0.1M, Sangon, Shanghai, China) and precipitated at -20°C overnight. Later, the samples were centrifuged at 12000g for 10min to collect precipitation and washing it with cold methanol (A456-4, ThermoScientific, Waltham, USA). The precipitation was collected by repeated centrifugation and methanol was replaced with acetone (LOT NO. 40064485, OKA, Shanghai, China). The samples were centrifuged at 12000 g for 10 min at 4°C to collect precipitation and the precipitation were dried at room temperature and dissolved in SDS lysis buffer (LOT NO. P0013G, Beyotime, Shanghai, China). Finally, the samples were centrifuged at 12000g for 10min to collect supernatants. The supernatant is the total protein of the sample. Then, the protein concentration was detected by BCA Kits (LOT NO. 23225, ThermoScientific, Waltham, USA). Protein quality was determined by 12% SDS-PAGE and digested with 0.1% trypsin. Then, the peptide was labeled with TMTpro reagent (LOT NO. A44521, ThermoScientific, Waltham, USA). All analyses were performed by a QE mass spectrometer (MS) (ThermoFisher, USA) equipped with an Easyspray source, the samples were sent to the precolumn Acclaim PepMap100 100 μm×2 cm (RP-C18, Thermo Fisher) at a flow rate of 300 nL/min and separated by analytical column Acclaim PepMap RSLC, 75μm×50cm (RP-C18, Thermo Fisher). The first-order MS mass resolution was set to 60000, the automatic gain control value was set to 3e6, the maximum injection time was set to 50 ms, the MS scanning was set to the full scanning charge/mass ratio (m/z) range of 350-1500, and 20 of the highest peaks were scanned by MS/MS. Proteome Discover 2.4 (Thermo Fisher) was used for database retrieval.

The amino acid sequences were retrieved from the Uniprot database according to the protein accession provided by proteomics (https://www.uniprot.org/). In the AllergenOnline database (http://www.allergenonline.org/), full-length sequences were retrieved by FASTA alignments, matching with known allergens, more than 50% were identified as potential allergens, and indicates the possibility of cross-reaction between them; more than 70% is considered to be susceptible to cross-reaction between them (Aalberse, 2000; Abdelmoteleb et al., 2021).

Sample preparation: 40 mg samples (4 replicates) were weighed into eppendorf tubes, 20 μL of L-2-chlorophenylalanine (LOT NO. C2001, HC Biotech, Shanghai, China) as internal standard (0.06 mg/mL, dissolved in methanol) and 1 mL mixture of methanol-water (vol/vol = 7/3) were added to each sample. The mixture was ultrasonic in ice bath for 30 minutes and rested overnight at -20°C. After centrifugation for 10 min (13000 rpm, 4°C), 150 μL supernatant was absorbed and filtered by 0.22 μm organic phase pinhole filter, and transferred to LC sample vial for LC-MS analysis. ACQUITY ultra performance liquid chromatography (UPLC) I-Class system (Waters, USA) coupled with VION IMS QTOF MS (Waters, USA) was used to analyze the metabolic profiling in both ESI positive and ESI negative ion modes. An ACQUITY UPLC BEH C18 column (1.7 μm, 2.1 × 100 mm) were used in both positive and negative modes. Water and Acetonitrile (LOT NO. A998-4, ThermoScientific, Waltham, USA)/Methanol 2/3 (v/v), both containing 0.1% formic acid were used as mobile phases A and B, respectively. The flow rate was 0.4 mL/min at 45°C of column temperature. All the samples were kept at 4°C during the analysis. The injection volume was 1 μL. Finally, data acquisition was performed in full scan mode (m/z ranges from 50 to 1000) combined with MSE mode and data were analyzed with reference to relevant literature (Liu et al., 2019).

As for proteomics: The LC-MS/MS raw data were imported in Maxquant for the analysis of labeling free quantification. Target-decoy-based error discovery rate (FDR) method is used to limit random peaks. The mass and strength of peptide peaks in mass spectrometry (MS) spectra were detected to identify peptides and assembled into three-dimensional (3D) peak hills over the m/z retention time plane, which are filtered by applying graph theory algorithms to identify isotope patterns. To achieve high mass accuracy, weighted averaging and mass recalibration (subtracting the determined systematic mass error from the measured mass of each MS isotope pattern) were conducted. Peptide and fragment masses were searched in an organism specific sequence database (including the target sequences, reverse counterparts and contaminants). About metabolomics: The original LC-MS data were processed by software Progenesis QI V2.3 (Nonlinear, Dynamics, Newcastle, UK) for baseline filtering, peak identification, integral, retention time correction, peak alignment, and normalization. Compound identification were based on precise mass-to-charge ratio (M/z), secondary fragments, and isotopic distribution using The PlantMADS Database (PMDB). The extracted data were further purified by removing any peaks with a missing value in more than 50% in groups, by replacing 0 value by half of the minimum value, and by screening according to the qualitative results of the compound (>36). A data matrix was combined from the positive and negative ion data. A combination of multidimensional analysis and one-dimensional analysis was used to screen different metabolites between groups. In OPLS-DA analysis, variable important in projection (VIP) can be used to measure the influence of the expression patterns of metabolites on the classification and discrimination of samples of each group, so as to explore the differential metabolites of biological significance. T test was further used to verify the significance of different metabolites between groups.

The mature pollen or poplar flocs was grinded in liquid nitrogen and extracted with phosphate buffer saline (PBS, 0.2M, pH 7.5) according to the ratio of solid to liquid 1:20 (g:mL, 4°C, 48h). The extract was filtered by filter paper to remove the residue and sterilized by a 0.22μm filter. The concentration of the extract was detected by BCA Kits. Thirty specific pathogen free (SPF) BALB/c mice were randomly divided into 3 groups (n = 10, license number: SCXK 2020-0005), which were PBS group, pollen group and poplar flocs group. Sensitized mice in pollen group and poplar flocs group were intraperitoneally injected with 10 µg total protein of pollen or poplar flocs extract [contains 4% Al(OH)₃] on day 0, 7, and 14, respectively; On the 21st day, pollen group and poplar flocs group were stimulated by 0.5 μg/mL pollen or poplar flocs extract for challenge, 30 min/time for one week; PBS groups were treated with equivalent volumes of PBS; 24h after the last stimulation, blood was taken from the eye socket in each group and placed it in a centrifuge tube (Figure 1B). After standing at 4°C for 2h, the serum was collected by centrifugation at 4000 g for 5 mins.

The plant protein extraction kit (LOT NO. C500053, Sangon,Shanghai, China) was used to extract the total protein of mature pollen/poplar flocs and protein concentration was detected by BCA Kits; 12% SDS-PAGE for 30 µg protein; the total protein was transferred to the nitrocellulose membrane and wash it 3 times with 1×tris-buffered saline with 0.1% tween 20 (TBST) [10×TBST (0.1 M Tris, 1.5 M NaCl, 1% Tween-20, pH7.5, LOT NO. C520009-0500, Sangon, Shanghai, China) was diluted with deionized water]. Then, the membrane was blocked with 5% non-fat milk in TBST for 2 h and wash it 3 times with 1×TBST. Afterward, the total protein of pollen was incubated with primary antibody (sensitized serum with poplar flocs), the total protein of poplar flocs was incubated with primary antibody (sensitized serum with pollen, diluted at 1:1000) at 4°C overnight, followed by washing 3 times with 1×TBST, HRP-labeled rabbit anti-mouse IgG (LOT NO. 6170-05 Amyjet, Wuhan, China) as secondary antibody (diluted at 1:1000), Incubated at room temperature for 2h.Wash the film with 1×TBST for 3 times, prepare the developing liquid A and B at 1:1 (LOT NO. BL520A, Biosharp, Guangzhou, China), and the film was exposed immediately on the Image System (ChemiDoc MP, Bio-RAD).

A total of 3914 identical proteins were identified from pollen and poplar flocs at different developmental stages (Supplementary 1); 564 differentially expressed proteins (DEPs) were involved in pollen maturation, among which 418 were up-regulated (multiprotein-bridging factor 1 MBF1, such as A0A2I4GFN0; NOI4-like protein, such as A0A2I4GL39; Cysteine proteinase inhibitor, such as A0A2I4EGF0), 146 down-regulated proteins(18KD heat shock protein, such as A0A2I4FG07 and A0A2I4FFZ4; 40S ribosomal protein, such as A0A2I4GHC8; Glucan synthase, such as A0A2I4F0F4). A total of 836 DEPs were involved in poplar flocs maturation, among which 397 were up-regulated (legumin B-like, such as A0A2I4GEI2; 11S globulin mainly, such as A0A1L6K371), and 439 were down-regulated(endoglucanase, such as A0A2I4GR72; GDSL esterase, such as A0A2I4EEB5). The expression trend of DEPs in pollen and poplar flocs at different developmental stages was stable (Figure 2).

Biological functions of DEPs were described by GO enrichment analysis. During pollen maturation, down-regulated proteins were mainly enriched in translation, response to heat, cytoplasm, ATP binding, structural constituent of ribosome, and ATP hydrolysis activity in terms of biological processes, cell components and biological functions (Figure 3A); the up-regulated proteins are mainly enriched in protein folding, intracellular protein transport, cytoplasm, mRNA binding, and translation initiation factor activity (Figure 3B). During poplar flocs maturation, down-regulated proteins were mainly enriched in protein transport, response to oxidative stress, cytoplasm, GTP binding, GTPase and peroxidase activity (Figure 3C); the up-regulated proteins are mainly enriched in translation, methylation, cytoplasm, RNA, mRNA and pyridoxal phosphate binding (Figure 3D).

KEGG enrichment analysis showed that the down-regulated proteins were mainly involved in ribosome, carbon, starch and sucrose metabolism during pollen maturation (Figure 4A), up-regulated proteins are mainly involved in Oxidative phosphorylation, Spliceosome, Endocytosis and other signaling pathways (Figure 4B). During poplar flocs maturation, down-regulated proteins are mainly involved in phenylpropanoid biosynthesis, endocytosis and pyruvate metabolism (Figure 4C), up-regulated proteins are mainly involved in signaling pathways such as ribosome, biosynthesis of amino acids, glyoxylate and dicarboxylate metabolism (Figure 4D).

According to metabolomics analysis, a total of 354 differential metabolites (DMs) were identified in the pollen group, which were mainly prenol lipids (15.32%) and flavonoids (14.81%). During pollen maturation, 249 DMs were up-regulated (such as albafuran C, gomphrenin II and sinensetin etc.) and 105 were down-regulated (such as dehydroanonaine, licoagroaurone and hydroxymyricanone etc.), among which the up-regulated DMs such as gnaphaliin, isoliquiritigenin, etc. and the down-regulated DMs such as Adenosine, D-Ribose etc. were considered to significantly affect pollen maturation (Supplementary 2). Moreover, 105 DMs have been identified during poplar flocs maturation, of which 42 are up-regulated (such as 8-Hydroxy-4’-methoxypinoresinol and capsianoside I etc.) and 63 are down-regulated (such as S-Allylcysteine and genistein 4’-O-glucuronide etc.), which main compounds are prenol lipids (14.49%) and organooxygen compounds (13.99%) (Supplementary 3). In pollen group, there was a significant correlation between different metabolites (P < 0.05, Figure 5A), as well as poplar flocs group (Figure 5B).

KEGG enrichment analysis showed that up-regulation of DMs in pollen group mainly involves in flavone and glutathione biosynthesis (Figure 5C); the down-regulation of DMs mainly involves in aminoacyl-tRNA biosynthesis, arginine biosynthesis (Figure 5D). Up-regulation of DMs in poplar flocs group mainly involved in citrate cycle, glutamate and phenylalanine metabolism (Figure 5E); the down-regulation of DMs mainly involves glycine, serine and threonine metabolism (Figure 5F).

According to sequence alignment in AllergenOnline database, 72 potential allergens from more than 10 protein families were identified. The amino acid sequences of potential allergens are more than 50% similarity to those of known allergens reported in the AllergenOnline database. Except for 11 allergens such as A0A2I4GA71, the expression levels of others were significantly different in different developmental stages of pollen and poplar flocs (Table 1).

To study the correlation between allergens and metabolites, integrated analysis was performed on the top 20 components in protein abundance and metabolite content. The results showed that there were significant correlations between allergens and metabolites in pollen group (r = -0.9999–0.9998, P < 0.01, Figure 6A), as well as the poplar flocs group (r = -0.9925–0.99701, P < 0.01, Figure 6B; Supplementary 4). Moreover, significant interactions were found among allergens, metabolites and allergen-metabolites in pollen group (Figure 6C) and poplar flocs group (Figure 6D; Supplementary 5).

The results of WB showed, no bands were found in total proteins of mature pollen and poplar flocs incubated with PBS sensitized serum. The total protein of mature poplar flocs incubated with sensitized serum showed obvious bands between 70-17KD, and the total protein of mature poplar flocs incubated with sensitized serum also showed the same characteristics (Figure 7).