An unexpected guest: Spirosoma a seed borne endosymbiont in hazelnut

Serious allergic reactions are increasing globally. Within this context, fatal anaphylaxis from hazelnut allergies is a critical public health concern. Hazelnuts, which are a common ingredient of many foods, contain many proteins that cause severe allergic reactions. Hazelnuts from all of the major commercial growing locations worldwide contained Spirosoma pollinicola sp proteins. This endotoxin-producing bacterium is linked to the allergenicity of hazelnut pollen. We were unable to remove the contamination by S. pollinicola proteins, showing that that this bacterium is a seed endosymbiont. Comparative proteomics revealed significant variations in the allergenic protein composition of nuts that correlated with patient immune responses. Hazelnuts from provenances 17 and 18 exhibited, lower levels of key antigens, particularly Cor a 9 and Cor a 14, highlighting their potential as candidates for genetic modification to mitigate allergenicity. Moreover, Spirosoma protein persistence may influence hazelnut allergenicity and the patient immune response.

Food allergies are persistent and potentially life-threatening health concern. The rising prevalence of food allergies in recent decades has led to significant clinical and societal challenges (Novembre et al., 2024). Public awareness of this issue is so acute that recent approval of a new drug for food allergy reached the front page of the New York Times (https://www.nytimes.com/2024/02/25/health/children-food-allergies-xolair.html). Fatal reactions to milk, peanuts and tree nuts are well recognized; however current gaps in understanding allergy pathogenesis hinder the ability to predict and prevent these events. (DuToit et al., 2024). Nuts, particularly tree nuts, are among the main causes of anaphylaxis in world populations and are ubiquitous in Western diets (Borres et al., 2022). There is currently no curative treatment for hazelnut allergy, and affected individuals must adhere to a restrictive diet and carry auto-injective epinephrine. The burden of nut allergies extends beyond physical health, significantly impacting psychological well-being by inducing stress and anxiety (Primeau et al; 2000). The rising prevalence of nut allergy further exacerbates these challenges, negatively affecting quality of life (Primeau et al; 2000; Avery et al., 2003; Arasi et a;/. 2023). Hazelnuts ( Corylus spp.) are key ingredient in widely consumed foods, particularly chocolate-based products, providing nutritional benefits and distinctive flavour. However, hazelnuts are also among the most potent food allergens, representing the leading cause of nut sensitization in general populations (Giannetti et al., 2023). The prevalence of hazelnut allergy is estimated at 0.86% in European adults, 0.28% in European children, 0.60% in American and Australian population (Calamelli et al., 2021). Hazelnut allergy is the fourth leading cause of food anaphylaxis in Europe, producing a wide array of symptoms, particularly in patients who are sensitized to highly stable allergens, such as seed storage proteins (Geiselhart et al., 2018). Compared to other types of food allergies, allergies to tree nuts, including hazelnuts, tend to persist throughout life, typically emerging between the age of 2 and 5 years. Allergic patients may react even to small quantities of food containing hazelnuts, with an eliciting threshold that is amongst the lowest in the field of food allergens. This is due to the extreme allergenic power of some of the hazelnut proteins, which are structural antigens (Hartz et al., 2010). Belonging to the Betulaceae family, hazelnut is a monoecious, self-incompatible wind-pollinated broadleaf species that typically thrives as an understorey shrub alongside birches and alders. The sporophytic self-incompatibility of the species is under the control of a single locus with multiple alleles (Bassil and Azarenko, 2001). Hazelnut cultivation has expanded globally in response to increasing industrial demand. The trees are generally propagated vegetatively via shoot or root cuttings, to mantain genetically uniformity and reduce propagation times. Corylus avellana L, the European hazelnut, and Corylus colurna L ., the Turkish hazelnut, are widely grown in Europe, and are important genetic resources for breeding programs. Seeds from ecologically and geographically diverse plants can harbour a characteristic range of microbiota, which are often identified by amplification and sequencing of genetic fragments. Epiphytic microbiota can consist of synergistic, commensal and potentially pathogenic microbes that play a crucial role in health and susceptibility to disease (Critzer & Doyle, 2010). Such microbiota that often reside on seed surfaces play functional role in plant growth, development and seed storage with seed-borne endosymbionts contributing to microbial populations within other plant tissues (Lucero et al ., 2011). Previous studies have identified Spirosoma pollinicola sp . nov., in the pollen of the European hazelnut (Ambika Manirajan et al., 2018). This endotoxin-producing bacterium is thought to contribute to the high allergenicity of hazelnut pollen, leading to the release of both chemokines and cytokines from epithelial A549 cells (Ambika Manirajan et al. 2022). Pollen associated bacteria may be transferred to seeds during pollination. Recent studies suggest that this allows the transmission of the plant microbiome across generation through the pollen grain, which acts as a vector for bacterial transfer to the developing seed (Cardinale et al., 2018). However, the potential impact of microbiome transfer on hazelnut allergenicity are currently unknown. Genomic data and proteomic data provide valuable insights for hazelnut breeding, particularly in effort to reducte allergenic protein content. RNA-seq characterization of complementary DNA (cDNA) libraries from four hazelnut tissues, including leaves, catkins, bark, and whole seedlings, led to the assembly of a 6.8 Gb hazelnut transcriptome (Rowley et al., 2012). De novo transcriptome assembly of C. avellana cv. Tombul, and C. colurna identified 70,265 and 88,343 unigenes, respectively (Ulu et al., 2023). Transcriptome data, whole-genome re-sequencing and ChIP sequencing and characterization of differentially expressed genes in the hazel genome have been applied to investigate the regulation of ovule and nut development (Cheng et al.2024). However, relatively few studies have explored the genetic variation and control of hazelnut allergens. A study involving 12 groups of allergenic proteins, and 13 hazelnut varieties revealed that all samples had similar IgE-reactivity profiles (Ribeiro, et al., 2020). Ten recognized hazelnut allergens are proteins (or glycoproteins): Cor a 1, Cor a 2, Cor a 8, Cor a 9, Cor a 10, Cor a 11, Cor a 12, Cor a 13, Cor a14, and Cor a 15 (Supplemental Table 1). Of these, Cor a 9, an 11S seed-storage globulin (legumin), Cor a 14, a 2S albumin, and – at a lesser extent – Cor a 8, a nonspecific lipid transfer protein, are associated with the most severe allergic reactions (Caffarelli et al, 2021). However, the genetic variability in the expression of these proteins in hazelnuts remains poorly studied and little information is available on how their abundance varies across different cultivars, particularly in response to environmental conditions. The following study was therefore conducted to investigate the extent of natural environmental and genetic variation in hazelnut allergen profile. Comparative proteomics revealed significant variations in allergenic protein composition among major commercial hazelnut-growing areas. These variations correlated with patient immune responses, as evidenced by the skin prick test results, underscoring the importance of cultivar selection in allergen management strategies. Surprisingly, we detected Spirosoma proteins in all nut samples, suggesting that this endosymbiont may influence hazelnut allergenicity .

Hazelnut samples used in this study come from different parts of the world, covering the main cultivation areas: Turkey, Italy, Chile, Azerbaijan and the USA. The nuts were sorted, cracked, shelled, calibrated before shipping, with stringent quality checks conducted analysis, in the same manner as they would be for roasting, processing and consumption. Preparation of defatted flour Raw hazelnuts were subjected to five cycles of grinding for two minutes each to achieve a fine texture. Following grinding, hazelnut flour was homogenized into a fine powder using a mortar and pestle to ensure uniform and smallest particle size. To prepare defatted hazelnut flour, one gram of hazelnut powder was extracted with five volumes of n-hexane, followed by a final defatting step using five volumes of acetone. Extractions were performed at 4 °C followed for 10 minutes followed by 30 minutes sedimentation and filtration. After defatting, hazelnut flour was air-dried under a fume hood to remove any residual solvent, Protein quality assessment Samples (100 mg) of defatted flour were extracted with 1.5 mL of sodium dodecyl sulphate (SDS) buffer (pH 6.8) as described by de Angelis (2022), with some modifications. Each sample was heated at 40 ◦ C for 20 min on a thermo-shaker (Thermomixer Comfort, Eppendorf- Netheler-Hinz GmbH, Hamburg) with a stirring function (1000 rpm), and then centrifuged. Supernatants were precipitated with cold 20% TCA/acetone. Pellet was subsequently washed with acetone twice and dissolved in 100 ul of Urea buffer (7M Urea, 0.1 M tris pH=8, 0.001M EDTA and 1% DTT), and used for protein estimation by Bradford. 15 ug of proteins were later separated on SDS PAGE acrylamide gradient gels (Any kD™ Mini-PROTEAN® TGX™ Precast Protein Gels). The remaining powder was subsequently used for shot gun proteome analysis. The protein extraction and all procedures for mass spectroscopy were performed by Biogenity ApS, Aalborg, Denmark, as follows. Powdered hazelnut samples were transferred to 1.5mL LoBind Eppendorf tubes containing 100 µL of lysis buffer (consisting of 6M Guanidinium Hydrochloride, 10 mM TCEP, 40 mM CAA, 50 mM HEPES pH8.5) and 3mm tungsten carbide beads (Qiagen). Samples were processed twice with the TissueLyser II (Qiagen) and 30µg of sample was diluted to 20µL with lysis buffer and taken forward for digestion and TMT labeling with 16plex tags (Thermo). Peptides were eluted over a 44-min gradient on a 15cm PepSep Endurance column (Bruker), and analysed with an Orbitrap EclipseTM TribridTM instrument (Thermo Fisher Scientific) with FAIMS ProTM Interface (ThermoFisher Scientific) switched between CVs of -50 V and -70 V with cycle times of respectively 2 and 1.5 s. Full MS spectra were collected at a resolution of 120,000, with normalized AGC target set to ‘standard’ or maximum injection time of 50 ms and a scan range of 375–1500 m/z. MS1 precursors with an intensity of >5×103 and charge state of 2-7 were selected for MS2 analysis. Dynamic exclusion was set to 120 s, the exclusion list was shared between CV values and Advanced Peak Determination was set to ‘off’. The precursor fit threshold was set to 70% with a fit window of 0.7 m/z for MS2. Precursors selected for MS2 were isolated in the quadrupole with a 0.7 m/z window. Ions were collected for a maximum injection time of 50 ms and normalized AGC target set to ‘standard’. Fragmentation was performed with a CID normalised collision energy of 30% and MS2 spectra were acquired in the IT at scan rate rapid. Precursors were subsequently filtered with an isobaric tag loss exclusion of TMT and precursor ion exclusion set to 25 ppm low and 25 ppm high. Precursors were isolated for an MS3 scan using the quadrupole with a 2 m/z window, and ions were collected for a maximum injection time of 86 ms and normalized AGC target of 300%. Turbo TMT was deactivated and number of dependent scans set to 5. Isolated precursors were fragmented again with 50% normalised HCD collision energy, and MS3 spectra were acquired in the orbitrap at 50000 resolution with a scan range of 100-500 m/z. MS performance was verified for consistency by running complex cell lysate quality control standard. The raw files were analysed using Proteome Discoverer 2.4 (Thermo Fisher Scientific). TMT reporter ion quantitation was enabled in the processing and consensus steps, and spectra were matched against the Corylus avellana obtained from UniProt. Dynamic modifications were set as Oxidation (M), Deamidation (N,Q) and Acetyl on protein N-termini. Cysteine carbamidomethyl (on C residues) and TMT 16-plex (on peptide N-termini and K residues) were set as static modifications. The data analysis The data were filtered to include only proteins with at least 2 unique peptides, 10% sequence coverage, and a minimum sequence score of 30. Data analysis was carried out using Perseus version 2.0.7 software (https://maxquant.net/perseus/). The dataset was filtered to retain proteins with at least 60% valid values across all samples, or at least 75% within each experimental group, and a cutoff of 100 for normalized intensity. The distribution of log2 ratio values of filtered data was analyzed as a frequency histogram. The data were symmetrically distributed and used for downstream analysis. Multi-sample ANOVA and two-sample T-tests were performed using Perseus with default settings (S0 = 0.1, false discovery rate = 0.05). Proteomics data are available in the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD052613 and 10.6019/PXD052613. (https://www.ebi.ac.uk/pride/review-dataset/1f7ba346d43f47b3a38f492d78ffa5e5, Project accession: PXD052613). Functional categories of hazelnut proteins by gene ontology The analysis of proteins functional profiles and KEGG pathway was based on the set of 372 proteins identified in all hazelnut samples. ID mapping of Uni Prot database (Release 2014_02) was used to find proteins GO terms. As a result, proteins were annotated with corresponding GO numbers, and then classified into biological process, cellular component and molecular function using ShinyGo 0.80 and g: Profiler. Spirosoma proteins Whole nuts were washed in water at 40 0 C foe 5 minutes and then with ethanol. This procedure was repeated three times, before the samples were extracted for proteomics analysis. In addition, other samples were soaked in bleach (10%) for 5 minutes before extraction for proteomics analysis. The proteomics analysis was performed as for the shelled hazelnuts, except that proteins were identified using the UNIprot database. Skin prick tests Skin prick tests were performed on 31 children, aged between 4 and 14 years, with an equal distribution of males and females and oral food challenge – confirmed hazelnut allergies. All tests were performed with ground hazelnut samples from 1-18 cultivars mixed with 0.9% saline. Samples were tested on the patients in duplicate. The appearance of a wheal with a mean diameter of at least 3 mm was considered a positive response. Skin reactivity was expressed by measuring the area of the wheals (Heinzerling et al., 2013). Detection of Spirosoma Hazelnuts samples were collected from 18 global commercial plantations (Figure 1 A, B). Proteomics analysis revealed the presence of Spirosoma in seeds from all the growing commercial regions (Figure 2). The bacterial proteins identified in hazelnut seeds included numerous metabolic enzymes, suggesting that Spirosoma remains viable within the seeds. Moreover, extensive washing or sterilization of the seed coat failed to remove these proteins, indicating a stable association with the seed microbiome. Sequence comparisons suggest that the proteins arise from Spirosomapollinicola sp. Nov, previously identified by genome-based comparisons between HA7 T and S. linguale DSM 74 T and S. fluviale DSM 29961 T (Ambika Manirajan et al. 2022). The hazelnut proteome Shotgun proteomics enabled the comprehensive profiling of the hazelnut proteome across commercial cultivars. Alignment of peptide sequences with established databases, including UniProt, Allergome, NCBI, and Ensembl Plants was used to identify all known allergens and their variants. Principal component analysis ( Figure 3) revealed that the hazelnuts proteomes varied according to the geographic location of origin. Tonda di Giffoni trees are cultivated in multiple regions (Italy, Chile and Georgia; location4, 6 and 14 respectively), while Tonda Gentile Trilobata is grown in Italy and Chile (location 5 and 8 respectively) and the Barcelona variety in Chile and the USA (location 7, 16 respectively). Some samples from different sources clustered closely (Figure 3, circles red and square green), which may reflect regional influences on proteomic composition. The overall structure of hazelnut proteome includes 1,216 proteins common to all samples (Figure 4 A, B). Additionally, 140 unique proteins were identified in one or more samples (Figure 4B). However, the normalized intensity values of these proteins were below the cutoff threshold of 100. They were therefore excluded from further analysis. Of the 1,216 common proteins, 621 were subjected to further analysis with 372 exhibiting significant differential abundance (Figure 4). Functional enrichment of gene ontology terms for the nut proteome identified 424 for Molecular function (MF), 809 for biological processes (BP) and 169 cellular components (CC; Supplemental Figures 1 and 2). A Gene Ontology (A, GO) function enrichment analysis of the hazelnut proteome (Supplemental Figure 2) revealed that of the 370 proteins that had statistically significant changes in protein abundance, many were involved in metabolism (e, g amylase, starch synthase) and defense (e.g. superoxide dismutase). Of the 212 proteins within the MF category (Supplemental Figure 2), many are involved in catalytic activity (GO:0140096), hydrolase activity (GO: 0008152), ATP binding (GO:0005524) and peroxidase activity (GO:0004601) as carbohydrate binding (GO:0030246). In addition, 84 proteins were in the category of biological processes including proteins involved in phosphorus metabolism (GO:0006793), response to stimulus (GO:0050896) and transport (GO:0006810). Only 25 proteins were classified in terms of cellular components including the apoplast (GO:0048046), membrane complexes (GO:0098796), cytoplasm (GO:0005737) and ribosome (GO:00057840). Pathway enrichment analysis revealed that many differentially expressed proteins in the hazelnut proteome were involved in nutrient reserve and energy metabolism, particularly involving malate, serine and glucose 6-phosphate pathways (Figure 5). Allergen identification Hazelnut allergens were identified based on the World Health Organization (WHO) and the International Union of Immunological Societies (IUIS) Allergen Nomenclature databases, alongside the Allergome lists of C. avellana allergens and iso-allergens (Supplemental Table 1).The detected allergens included Cor a 1 (Bet v 1 homologue), Cor a 2 (profilin), Cor a 8 (lipid transfer protein (LPT), Cor a 9 (11S legumin), Cor a 11 (7S vicilin), Cor a 14 (2S albumin) and the oleosins Cor a 12, Cor a 13 (oleosin protein types) and Cor a 15 (7S vicilin-type seed storage protein), Cor a 16 (2S albumin) and Cor a thaumatin-like protein (TLP) (https://www.allergome.org/script/search_step2.php). Stringent selection criteria were applied to ensure reliable and significant allergen identification: a minimum sequence coverage of 10%, at least two unique peptides, and a sequence score higher than 30. An exception with a lower coverage of 12% was Cor a 16; however, the high number of unique peptides associated provided confidence in its identification. A second exception was Cor a TLP, which is a minor allergen that is recognized by less than 10% of hazelnut allergic patients (Palacín et al., 2012). In the present analysis this protein was identified with low confidence, based only on 1 unique peptide, and with 6% coverage by all identified peptides. It was therefore not subjected to further analysis (Table 1). Iso-allergens and allergens variants Most allergens including Cor a 6, Cor a 8, Cor a 10, Cor a 13, Cor a 14, and Cor a 15 were represented by only one isoform, as identified by a single variant (Table 1). In contrast, Cor a 1 was represented by multiple isoforms (Cor a 1.0101 to Cor a 1.0801: Allergome database). Three isoforms were identified in the 18 samples: Cor a 1.0401, Cor a 1.0402, and Cor a 1.0501. Some allergens, including Cor a 2 Cor a 9 and Cor a 11 were represented by two or more isoforms: Cor a 2, Cor a 2.0101; Cor a 9, Cor a 9.0101 and Cor a 11.0101, Cor a 11.0102, respectively. Each pair of isoforms exhibited a high degree of homology (98%), in which sequences differed only in few amino acids. Cor a 2 and Cor a 11 are encoded by single gene, while the two isoforms of Cor a 9 are encoded by two different genes (Costa et al., 2016). Of the three Cor a 16 isoforms listed in the Allergome database, only one isoform was detected in the hazelnut samples tested subjected to the present analysis (Table 1). Cultivar-dependent variations in allergen composition Cor a 9 and Cor a 11 were more abundant than other allergens in all samples, while Cor a 1.05, Cor a 2, Cor a 11.0102 and Cor a 13.0101 were the lowest in abundance (Figure 6). Significant differences in the relative abundance of the Cor a 1, Cor a 2, Cor a 9, Cor a 11 and Cor a 12 iso-forms were observed, with Cor a 11 being the most abundant (Figure 6). Levels of Cor a 11.0101 were 60% higher than Cor a 11.0102 (Figure 6). Cor a 8, 9, 11, and 14 accounted for only about 1-4% of the total nut protein (Figure 6). Hierarchical clustering of the nut allergens revealed significant differences in the abundance of the proteins between some of the samples (Figure 7). Pairwise comparisons identified significant differences in the levels of major allergens between two or more cultivars. For simplicity, the variations in relative abundance between samples is shown only for the four main allergens (Figure 8). For example, the levels of Cor a 9.0101 were significantly lower in samples 4, 14 and 17, while Cor a11 levels were significantly lower in samples 5 and 8. Conversely, Cor a 8 iso-forms were most abundant in samples 12 and 18 (Figure 8). Variations in immune responses to hazelnut cultivars Skin prick test analysis on patients with hazelnut allergies revealed variations in the average wheal sizes and hence responses to the nut extracts from the 18 sample of 6 growing areas: Azerbaijan, Chile, Georgia, Italy, Turkey and USA (Figure 9a). Weaker immune responses were observed in cultivars 8, 18 and 14, which had lower levels of Cor a 9.0101 and Cor a11 levels than other samples, compared to other cultivars. In contrast, cultivars 2, 10 and 11 showed much stronger responses (Figure 9a). Relationships between the skin prick tests and allergens levels between the 18 growing regions was further analysed using the Pearson correlation statistic method. For most of allergens the correlations were weak or negligible (R s range –0.22 to 0.34, P value range .04 to .86l Figure 9b, c). However, a positive statistically significant corelation was observed for Cor a 9 (R s = 0.59; P value=0.0097) and Cor a 9.0101 (R s = 0.48; P value=0.042) (Figure 9 A, B, C).

The global hazelnut supply chain requires high-quality supplies of fresh hazelnuts throughout the year. In addition to existing cultivation areas, new plantations are emerging in countries such as Chile, Oregon, Georgia and the Balkans. Nuts from all commercial sources contained Spirosoma as an endosymbiont suggesting the universal nature of the relationship between the bacteria and the nuts. Our findings provide the first evidence that all commercial sources of hazelnuts contain Spirosoma as an endosymbiont that is likely to be transferred through the pollen. While such microbiota often resides on the seed surfaces and are often identified by amplification and sequencing of genetic fragments, the data presented here reveal the presence of Spirosoma proteins within the nuts, because they were not removed by repeated washing or sterilisation. Although the functional significance of the presence of Spirosoma proteins remains unclear it is possible that their presence may influence the overall protein composition of the hazel nut seeds. This finding lays the foundations for further investigations into the interactions between the microsymbiont and its host that influence nut allergen contents. In addition, the observed genotypic variation in protein composition provides novel insights into genotype/environment interactions that influence the nut proteome. We have identified small but important variations in the protein composition of hazelnuts from the different commercial provenances. While processing can significantly decrease the levels of individual nut allergens (Cuadrado et al, 2021), the protein composition of the nuts is inherently dependent on genetic components and their regulation. Proteomics approaches have previously been used to analysis the effects of processing in reducing the allergenicity of hazelnut proteins (De Angelis et al., 2022) and evaluate the allergenic potential of 13 genetically diverse sets of hazelnuts (Ribeiro et al., 2020). Interestingly, despite the genetic diversity of hazelnut varieties and possible variety-dependent differences in the IgE-binding properties, only minor differences were found at the level of genes encoding Cor a 8, Cor a 9 and Cor a 14 in the 13 hazelnut varieties tested (Ribeiro et al., 2020).The shotgun proteomics approach undertaken in the present study would largely support this conclusion, however small but significant differences in the levels of major allergens were revealed among cultivars. Moreover, principal component analysis revealed significant proteome variations associated with both geographical origin and genetic background. Notably, the levels of some allergens such as Cor a 9.0101 were significantly lower in some samples (4, 14 and 17), while Cor a 8 iso-forms were most abundant in samples 12 and 18 (Figure 7). Further research is required to determine the full significance of such differences for the overall allergenicity of the hazelnuts. In the interests of time, this study did not focus on all the 1,216 proteins present in all nut samples, or the 140 unique proteins that were identified in one or more samples, but these data could be useful in revealing the molecular and metabolic mechanisms that underpin the observed differences in allergen levels. Importantly, our study found the variations in the accumulation of allergens correlated with variations in the immune reactions among patients. The skin prick tests reported here revealed variations in the intensity of immunological reactions that correlated with the abundance of both Cor a 9 iso-allergen. Given the semi-quantitative nature of the measurement of this parameter, further studies involving larger patients cohorts are required to fully explore the relationships between the levels of allergens in different samples and the intensity of immune reactions. The data presented here have identified provenances 17 and 18, as having lower levels of key antigens, making them prime candidates for genetic interventions aimed at decreasing the levels of specific antigens. This is a crucial next step in plant allergen science because many of the major allergens in hazelnuts and other tree seeds are heat stable and hence highly resistant to degradation during processing. Hazelnut in vitro cultures are used for commercial production of secondary metabolites such as paclitaxel (Gallego, et al ., 2017). In addition, hazel plantlets can be regenerated from callus tissues by differentiation induced by exogenous growth regulators (Salehi, et al., 2017). It should therefore be possible to ectopically express transcription factors that regulate totipotency and stimulate cell proliferation (Jha & Kumar, 2018), while silencing other transcription factors in order to stimulate plantlet formation and accelerate flowering. CRISP-CAS technology can then be used to decrease the expression of specific allergenic proteins in the hazelnut seeds. Finally, our findings confirm that hazelnut seeds from ecologically and geographically diverse commercial trees can harbour Spirosoma pollinicola. Although the functional significance of this endosymbiont for the growth and development of the trees is unknown, this transfer facilitates the presence of Spirosoma pollinicola in the pollen of the next generation. Hence, the effective removal of the bacteria from the pollen would therefore require a stringent endosymbiont elimination from the seeds. A deeper understanding of the seed microbiome is thus essential in devising strategies to mitigate allergenicity of plant organs. LEGENDS TO FIGURES Figure 1. Hazelnut production areas (A) and geographical locations (B) Figure 2. Summed intensities of Spirosoma proteins (A) and identification of Spirosoma proteins in samples 1–18 (B) Figure 3. Principal component analysis (PCA) of hazelnuts sample from commercial growing areas in Azarbaijan, Chile, Georgia, Italy, Turkey and the USA. Figure 4. Heatmap of total identified proteins (A). The presence of individual proteins in the 18 hazelnut samples (B). Figure 5. Pathway enrichment analysis of the hazelnut proteome Figure 6 . Relative abundance of identified allergens in nuts from the 18 cultivated growing areas. Figure 7 . Hierarchical clustering of allergenic proteins from the 18 cultivated growing areas. Figure 8. Box plots showing the relative abundance of the four main allergens: Cor a 8 Cor a 9.0101, Cor a 11.0101 and Cor 14. Different letters indicate significant differences at P < 0.05. Figure 9. Skin prick tests showing the average wheal diameter of immunological response (A); Pearson correlation coefficient ( r ) showing the correlation between allergen abundance and mean wheal size of skin prick test (B). Correlation plots for Cor a 9.0101 (B) and Cor a 9 (C): p-values 0.0097 and 0.042, respectively. Supplemental Figure 1. Functional enrichment of GO terms for MF (Molecular function), BP (Biological processes) and (CC) cellular component for whole proteome. 424 GO-terms are presented for MF, 809 for BP and 169 for CC. Analysis was performed using https://biit.cs.ut.ee/gprofiler/. Supplemental Figure 2. Gene Ontology (A, GO) function enrichment analysis of the hazelnut proteome, in which 370 proteins had statistically significant changes in protein abundance. GO categories: molecular function (MF), biological processes (BP) and cellular component (CC). Supplemental Table 1. List of major hazelnut allergens detected in the commercial samples Author contributions: Barbara Karpinska (BK) undertook all the experimental work, except for the skin prick tests, which were performed by Alessandro Fiocchi (AF). BK analyzed the data, prepared the figures for the manuscript. AF discussed the data and helped to prepare the manuscript. Christine H Foyer (CHF), Ileana Manera, Marta Biolatti and AF had the original concept. All authors designed the studies and discussed the data. CHF wrote the manuscript. All authors assisted with reviewing and editing the manuscript. Acknowledgments: This study would not have been possible without the commitment of Dr. Enrico Pavesi and Dr. Roberto Menta, Soremartec Italia S.r.l. We thank Dr. Veronica Calandrelli for her help with the management of the in vivo pin-prick tests. Funding statement: The research was financially supported by Soremartec Italia S.r.l, Ferrero Group. We also thank the Group for fostering the collaboration between AF, BK and CHF. Declaration of interest statement There are no conflicts of Interest Data availability Statement Proteomics data are available in the ProteomeXchange Consortium via the PRIDE partner repository with the dataset identifier PXD052613 and 10.6019/PXD052613. (https://www.ebi.ac.uk/pride/review-dataset/1f7ba346d43f47b3a38f492d78ffa5e5, Project accession: PXD052613).

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Authors Metrics & Citations Metrics Article Usage 344views 247downloads Citations Download citation Barbara Karpinska, Alessandro Fiocchi, Marta Biolatti, et al. An unexpected guest: Spirosoma a seed borne endosymbiont in hazelnut. Authorea. 09 June 2025. DOI: https://doi.org/10.22541/au.174945082.28599434/v1 DOI: https://doi.org/10.22541/au.174945082.28599434/v1 If you have the appropriate software installed, you can download article citation data to the citation manager of your choice. Simply select your manager software from the list below and click Download. For more information or tips please see 'Downloading to a citation manager' in the Help menu.