Rethinking spillover risks: first description of the Vespa orientalis gut microbiome and its impact on honeybee and human health

Rethinking spillover risks: first description of the Vespa orientalis gut microbiome and its impact on honeybee and human health | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Rethinking spillover risks: first description of the Vespa orientalis gut microbiome and its impact on honeybee and human health Simone Cutajar, Chiara Braglia, Daniele Alberoni, Martina Mifsud, and 4 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6179679/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Vespa orientalis (Oriental hornet) is expanding its range worldwide, raising concerns about its predatory impact on honey bees and potential health risks to humans. This study provides the first comprehensive description of the V. orientalis gut microbiome, explores how diet and location influence microbial composition, and bee pathogens reservoir. Adult hornets with different feeding behaviors were sampled from four urban and natural sites in Malta. 16S rRNA gene sequencing revealed a gut microbiota dominated by Firmicutes and Proteobacteria, with key genera including Carnimonas , Arsenophonus , and Rosenbergiella. Significant compositional shifts were observed in relation to diet and sampling location, suggesting that environment and diet significantly shape the hornet gut community. Moreover, detection of certain honey bee-associated microbes, such as Gilliamella and Snodgrassella , points to potential microbial exchange between predator and prey. Quantitative PCR targeting bee and human pathogens detected high prevalence rates of Nosema ceranae , Crithidia bombi , and Serratia , while Listeria , Salmonella , and other bee pathogens were absent. Our findings suggest V. orientalis may function more as a pathogen reservoir rather than a primary spillover vector and lays the groundwork for targeted management strategies to mitigate its impact on apiculture and broader ecosystem services. Spiroplasmataceae Enterobacter Arsenophonus Crithidia Nosema spillback Figures Figure 1 Figure 2 Figure 3 Introduction Vespa orientalis , commonly known as the Oriental hornet, is a large eusocial insect belonging to the Vespidae family. It is native to the southeastern Mediterranean region, including Malta, southern Italy, Cyprus, as well as northeastern and eastern Africa, the Middle East, and Central Asia [ 1 – 3 ]. This species has gained attention for its expanding range, via accidental human-assisted introductions [ 4 ], and its ecological impact, particularly its interactions with honey bee populations [ 5 ]. V. orientalis typically establishes colonies in underground nests and preys on honey bees and other insects, raising concern among beekeepers [ 6 ]. In addition to posing a threat to beekeeping and native biodiversity, V. orientalis may also impact public health. As an opportunistic feeder, this hornet regularly comes into contact with raw or decaying proteins (e.g., meat, cat food), as well as sugar-rich materials (e.g., fruits, honey) [ 7 ]. These diverse feeding behaviours make V. orientalis a frequent presence in urban and peri-urban environments [ 4 , 8 ]. Because they often forage in close proximity to human activities, there is an increased likelihood of harbouring and transmitting microbes relevant to human health. To date, V. orientalis has been reported in numerous non-native regions, including previously uncolonised areas of Europe, as well as South America (Brazil and Chile) [ 9 ], and North America (Mexico) [ 10 ]. In Europe, it was first recorded in Spain in 2012, where it is now considered established [ 11 , 12 ]. Subsequent detections have been reported in Romania [ 13 ], France [ 14 ], northern Italy [ 8 , 15 ] and the Greek islands [ 16 ]. This broad distribution across distant regions suggests that V. orientalis possesses biological traits that enhance its invasion potential [ 4 ]. In Malta, where V. orientalis is considered indigenous, its adverse impact on apiculture has increased in recent years ( Survey Appendix 1 ), alongside an extended period of activity [ 6 ]. This increased predation on honey bees, which, in severe cases, can lead to entire colony collapse [ 6 ], has raised concerns that V. orientalis is exhibiting invasive behaviour in its native range. Its presence threatens pollination services, biodiversity, agricultural productivity, and apiculture. The recent spread and increased impact of V. orientalis , even in its native range, have been linked to climate change, human-mediated dispersal, ecological shifts, urbanisation, and weakened honey bee colonies. Rising temperatures and milder winters enhance queen survival [ 17 ], while global trade facilitates unintentional introductions [ 4 ]. Urbanisation creates new nesting sites, and weakened honey bee colonies, affected by pesticides, habitat loss, and diseases, become more vulnerable to predation. These factors, combined with high propagule pressure, adaptability to human-altered environments, and human-assisted dispersal, allow V. orientalis to establish in new ecological niches, posing a growing threat to local ecosystems [ 4 ]. Recent studies have highlighted the fundamental role of the gut microbiome in social insects, influencing health, nutrition, immunity, and adaptability [ 18 ]. While research has explored the microbiomes of hornet species such as Vespa mandarinia, Vespa simillima [ 19 ] and Vespa velutina with its subspecies V. velutina subsp. nigrithorax and V. velutina subsp. auraria [ 20 , 21 ]; no published studies have characterised the gut microbiota of V. orientalis . Increasingly, studies on other social insects have shown that gut microbiota is strongly influenced by environmental factors and diet, shaping their adaptability and ecological interactions [ 22 , 23 ]. Understanding these microbial communities is particularly important in a species with global invasive potential, as it poses risks both as a honey bee predator and as a potential pathogen reservoir for honey bees and humans [ 5 , 24 ]. By analysing hornets from four sites in Malta, including individuals feeding on honey bees near apiaries and scavenging on cat food in urban and peri-urban habitats, this study aims to characterise the gut microbiota and potential pathogens of V. orientalis , while distinguishing the effects of diet and environment on microbiome composition. Given its expanding range, evaluating V. orientalis 's potential health risks is of growing concern, particularly in the context of pathogen transmission to honey bees, other insects, and even humans. A One Health approach, which integrates the interconnected health of pollinators, ecosystems, and public health, provides a broader framework for assessing these risks. Since V. orientalis may facilitate microbial exchanges across species, studying its gut microbiota could reveal pathogen transmission pathways and contribute to sustainable management strategies, including the development of microbial-based biological control methods. Materials and Methods 2.1 Beekeeper Survey Data Collection To assess the perceived impact of V. orientalis on beekeeping in Malta, survey data were collected by the Malta Beekeeping Association (MBKA, VO 1527) from 2022 to 2024. The surveys aimed to document beekeeper-reported observations, colony and brood losses, mitigation efforts, and the effectiveness of control measures. The dataset was compiled from voluntary responses by MBKA members, representing a longitudinal perspective on the species' effects on apiculture in Malta. The survey provides insights into yearly variations in V. orientalis apicultural impact and beekeeper interventions. Each annual survey contained a structured set of questions designed to capture key trends, such as reported colony losses attributed to hornet predation, and beekeeper interventions to mitigate the threat. While the questionnaire evolved slightly over the three-year period, core questions remained consistent to allow for comparative analysis. The responses were compiled, anonymised, and provided by the MBKA for integration into this study. The surveys were conducted in Maltese and subsequently translated into English by the study authors to ensure consistency and clarity in data interpretation. Survey results were analysed to detect changes in hornet impact over time and assess the effectiveness of control measures. 2.1 Samples Collection Adult V. orientalis individuals ( Figure S1 , and Supplementary Appendix 2 ) were collected from four site types categorised by dominant food source: ‘honey bee’ sites (locations with active apiaries) and ‘cat food’ sites (urban locations where hornets scavenging pet food). Sampling was conducted between September and October 2023 at four localities; an urban site in Imsida (VoU, University of Malta campus – 35°54'01"N 14°28'59"E), a peri-urban site in Qawra (VoQ – 35°56'50"N 14°25'19"E), a peri-urban San Ġwann site (VoS – 35°54'26.6"N 14°27'49.3"E), and a natural site in Gudja (VoG – 35°51'18"N 14°30'35"E). In each site ( Figure S2 ), hornets were captured randomly using a sweep net or an electric fly swatter, for a total of 70 samples. Specimens were placed on ice immediately after collection and transported to the University of Malta, where they were stored at − 80°C. They were then shipped frozen to the University of Bologna for molecular analysis. 2.2 DNA Extraction Prior to DNA extraction, adult hornets were dissected at controlled temperature near 0°C, by using ethanol-sterilised forceps. The last abdominal segment was carefully removed along with the entire gut and transferred into a sterile 1.5 mL Eppendorf tube. A total of 70 gut samples were processed for microbial DNA extraction according to [ 25 ]. DNA was extracted using the PureLink™ Genomic DNA Mini Kit (Thermo Fisher Scientific), following the manufacturer’s protocol. The extracted DNA was quantified using a Qubit dsDNA HS Assay Broad Range Kit (Thermo Fisher Scientific). 2.3 Library Preparation and Sequencing Library preparation and sequencing were performed by IGA Technology Services S.r.l. (Udine, Italy). The 16S rRNA V3-V4 region was targeted for amplicon sequencing, using Illumina MiSeq technology. Each sample was sequenced with a target depth of 50,000 reads per sample. The sequencing service included PCR amplification, library preparation, and quality control (QC) checkpoints. Samples were directly processed through PCR amplification, and only successfully amplified libraries were used for sequencing. The sequencing platform was optimised to ensure a minimum of 95% of the target sequencing output (expressed in millions of reads). 2.4 Quantitative Polymerase Chain Reaction (qPCR) The absolute quantification of bee pathogens ( Nosema ceranae , N. apis , N. bombi , Serratia , Crithidia bombi , C. mellificae , Lotmaria passim , Apicystis bombi ), human pathogens ( Listeria and Salmonella ), and total bacteria were quantified with specific primers listed in Supplementary Table S1 . The PCR products for each target were purified with NucleoSpin® Gel and PCR Clean-up (Macherey-Nagel), quantified with Qubit dsDNA Broad Range kit (Thermo Fisher Scientific) and converted in total amount of copies per microliter. Purified PCR products were used to generate standard curve-based quantification, obtained with serial dilution of the pre-amplified target amplicons (10 4 to 10 8 copies). Quantitative PCR protocols were carried out with QuantStudio® 5 Real-Time PCR System (Applied Biosystems), according to [ 26 , 27 ]. Amplifications of each microbial target were carried out using PowerUp SYBR Green Master Mix (Applied Biosystems) in a final volume of 10 µL. Data were converted according to the respective rRNA copy number to obtain the absolute quantification of targeted microorganisms expressed in Log spores/gut for Nosema , Log cells/gut for C. bombi , Log luxS gene copies/gut for Serratia , and Log 16S rRNA copies/gut for the total bacteria. 2.4 Bioinformatics Raw sequencing reads were processed using QIIME2-amplicon-2024.2 [ 28 ]. After importing data we eliminated samples with sequences less than 100,000 reads. The DADA2 plugin was used for read joining, denoising, and chimera filtering. Taxonomic classification was performed using the Silva 138.1 database [ 29 ] with the plugin qiime feature-classifier using vsearch (classify-consensus-vsearch) , employing a full-length sequence classifier. Before visualization using qiime taxa barplot, taxonomic assignment and representative sequences were filtered for “Mitochondria”, “Chloroplast”, and “Unassigned” using plugin qiime taxa and the methods filter-table and filter-seqs . Phylogenetic relationships were inferred by constructing a rooted tree using qiime phylogeny align-to-tree-mafft-fasttree . Alpha and beta diversity analyses were conducted using this rooted tree and 16710 as sampling-depth. Rarefaction curves were generated with qiime diversity plugin and the visualizer alpha-rarefaction . 2.5 Core Microbiota Determination To identify the core gut microbiota of Vespa orientalis , bacterial taxa consistently present across samples at a predefined prevalence threshold were considered. Microbial presence was assessed at the Amplicon Sequence Variant (ASV) level, and prevalence (%) was calculated as ( number of samples where the taxon is present / total number of samples ) × 100. In this study, core gut microbiota was defined as taxa detected in at least 80% of samples (across all locations) with a relative abundance greater than 1%, following established thresholds [ 19 , 30 ]. 2.6 Statistical Analysis All statistical analyses were conducted using QIIME2-amplicon-2024.2 [ 28 ] and R version 4.3.3 (R foundation for Statistical Computing; Vienna, Austria) to assess microbial diversity and composition across different food sources and geographic locations. Alpha diversity was assessed to evaluate microbial richness and evenness within samples using three indices: (i) Faith’s Phylogenetic Diversity (Faith PD), which accounts for evolutionary relationships between taxa; (ii) Observed Features, representing the number of unique bacterial taxa per sample; and (iii) Pielou’s Evenness, which quantifies the uniformity of taxa distribution within a sample. Differences in alpha diversity between groups were assessed using the Mann-Whitney U test, a non-parametric approach suitable for comparing microbial diversity across independent groups. To account for multiple comparisons, Bonferroni correction was applied. To examine differences in microbiota composition among sites and diets, beta diversity was analysed using both Weighted and Unweighted UniFrac distances, which consider both phylogenetic relationships and relative abundances of bacterial taxa. PERMANOVA (Permutational Multivariate Analysis of Variance) with 999 permutations was used to determine whether microbial community composition varied significantly between groups. Beta diversity patterns were visualized through Principal Coordinates Analysis (PCoA) and non-metric multidimensional scaling (NMDS) based on Bray-Curtis dissimilarity. Differential abundance analysis was performed using plugin qiime composition, the method ancombc and the visualizer da-barplot to show bacterial taxa that were enriched in different groups. This method was selected for its ability to account for compositional data biases while providing robust estimates of differential abundance. A log fold change (LFC) threshold of ± 1.5 was applied to define relevant differences. Finally, to compare the relative abundance from NGS data and the absolute abundance of total bacteria, and the honey bee and human pathogens from qPCR data, one-way ANOVA with Tukey HSD [ 31 ] post-hoc test was applied for normally distributed data with homoscedasticity. On the other hand, Kruskal–Wallis one-way ANOVA with Dunn’s multiple comparisons post-hoc test was used for non-normal distributed data [ 32 , 33 ]. Shapiro-Wilk [ 34 ] test and Levene test [ 35 ] were used to assess data distribution and homoscedasticity. All statistical analyses were conducted at a significance threshold of p ≤ 0.05, with appropriate corrections applied for multiple comparisons. Results 3.1 Beekeeper Survey Results The beekeeper survey data collected from 2022 to 2024 provide insights into the perceived impact of V. orientalis on apiculture in Malta. A total of 58 beekeepers responded in 2022, 34 in 2023, and 37 in 2024, allowing for a comparative analysis of trends over time. In each survey year, all responding beekeepers (100%) reported V. orientalis sightings in their apiaries. Reported colony losses due to hornet predation followed a similar pattern, with 37 cases in 2022 (63.8% of respondents), dropping to 10 in 2023 (29.4%), and rising again to 22 in 2024 (59.5%). The decline in 2023 suggests a temporary reduction in hornet impact, though losses rebounded the following year. Beekeepers reported various intervention efforts to control V. orientalis , including trapping of queens and/or drones and manual removal. In 2022, 48 beekeepers (82.8%) took action against the hornet, decreasing to 25 (73.5%) in 2023 and 28 (75.7%) in 2024. This decline in intervention rates may indicate reduced beekeeper engagement or shifts in hornet population dynamics. Assessments of intervention effectiveness varied. In 2023, 18 beekeepers (52.9%) considered their efforts effective, while four (11.8%) reported complete failure. By 2024, the number of beekeepers who found interventions successful dropped to 16 (43.2%), while those reporting failed control measures increased to seven (18.9%). This suggests that traditional mitigation strategies may be losing efficacy over time. Overall, these survey findings suggest that although V. orientalis sightings have remained consistently high, colony losses persisted, and beekeeper interventions became less frequent and less effective. The pronounced reduction in colony losses in 2023 appears to have been short-lived, as evidenced by the resurgence in 2024. The increase in failed interventions in 2024 raises concerns about the growing impact of V. orientalis on beekeeping in Malta. 3.2 Next-Generation Sequencing (NGS) Output Results High-throughput sequencing of V. orientalis gut samples generated a total of 2,964,602 clean paired reads, ranging from 16,710 to 83,316 paired reads per sample. Microbial community analysis using QIIME2-amplicon-2024.2 identified 7,309 Amplicon Sequence Variants (ASVs). To ensure uniform comparisons across samples, all data were subsampled to the study’s minimum sequencing depth (50,000 reads), a threshold expected to have minimal impact on downstream analyses. This led to the exclusion of five samples (VoGB6, VoGBa2, VoGB10, VoGB19, and VoGB3). 3.3 Microbial Community Composition in Vespa orientalis Phylogenetic classification revealed that the gut microbiota of V. orientalis was predominantly composed of Firmicutes (71.8% relative abundance), followed by Proteobacteria (22.2%), Actinobacteriota (1.91%), Bacteroidota (0.70%), and Cyanobacteria (0.41%). Other phyla collectively accounted for less than 9.68% of the total relative abundance. At the family level, the most dominant taxa were Spiroplasmataceae (67.05%), Morganellaceae (9.50%), Erwiniaceae (4.55%), and Leuconostocaceae (2.18%, Supplementary Figure S3 ). At the genus level, the most abundant taxa included Spiroplasma (67.05%), Arsenophonus (9.50%), and Rosenbergiella (4.22%, Fig. 1 ). A complete summary of relative abundance percentages at the phylum, family, and genus levels is provided in Supplementary Table S2 . 3.4 Determination of Core Gut Microbiota in Vespa orientalis Our results indicate that the core gut microbiota of V. orientalis at the family level consists of Spiroplasmataceae (PS = 1.00), Morganellaceae (PS = 1.00), Halomonadaceae (PS = 1.00), Erwiniaceae (PS = 1.00), Burkholderiaceae (PS = 1.00), Moraxellaceae (PS = 0.99), Leuconostocaceae (PS = 0.99), and Microbacteriaceae (PS = 0.93) ( Supplementary Figure S4 ). At the genus level, the core microbiome includes Carnimonas (PS = 0.94), Halomonas (PS = 0.97), Arsenophonus (PS = 1.00), Fructobacillus (PS = 0.89), Spiroplasma (PS = 1.00), Lactococcus (PS = 0.93), Acinetobacter (PS = 0.99), Rosenbergiella (PS = 1.00), Burkholderia (PS = 1.00), and Leifsonia (PS = 0.93) (Fig. 2 ). To illustrate the genus-level distribution of core taxa across individual samples, a heatmap was generated ( Supplementary Figure S5 ), depicting relative abundance patterns across the four sampling sites. A complete list of prevalence and abundance scores is provided in Supplementary Table S3 . 3.5 Landscape Impact on the Gut Microbial Community Alpha-diversity analysis measured using Faith’s Phylogenetic Diversity (Faith PD), Observed Features, and Pielou’s Evenness, indicated no significant differences in species richness across sites. However, Faith PD values resulted significantly different comparing San Ġwann and Imsida ( p < 0.05). Beta-diversity analysis using Weighted UniFrac distances showed that gut microbial composition significantly differed by location (PERMANOVA: p = 0.001). Pairwise comparisons highlighted distinct clustering between Gudja vs Imsida (p < 0.01) and Gudja vs San Ġwann (p < 0.05). Additionally, PCoA analysis indicated that Gudja samples formed a separate cluster, suggesting a strong influence of local environmental conditions on gut microbiota. At the phylum level, Firmicutes were significantly more abundant in Imsida compared to Gudja (p < 0.05), while Proteobacteria showed a higher abundance in Gudja than in San Ġwann (p < 0.05) and Imsida (p < 0.01). At the family level, Erwiniaceae and Morganellaceae were more abundant in Gudja hornets than in San Ġwann (p < 0.05 for both) and Imsida (p < 0.05 and p < 0.01, respectively). On the other hand, Spiroplasmataceae levels were lower in Gudja compared to Imsida (p < 0.05). At the genus level, Arsenophonus and Rosenbergiella were significantly enriched in Gudja hornets compared to those in San Ġwann (both p < 0.05) and Imsida (p < 0.01 and p < 0.05, respectively). Conversely, Spiroplasma levels were lower in Gudja compared to Imsida (p < 0.05). Differential Abundance Analysis (DAA) revealed site-specific differences in microbial taxa. In Gudja vs. Imsida, Arsenophonus was significantly more abundant in Gudja, whereas Spiroplasma , Hafnia-Obesumbacterium , Serratia , and Enterobacter were more common in Imsida samples (Log fold change = ± 3, Supplementary Figure S6 ). Comparisons between Gudja and San Ġwann showed that Arsenophonus , Rosenbergiella , Dysgonomonas , Gluconobacter , and Acinetobacter were enriched in Gudja, while Hafnia-Obesumbacterium was significantly higher in San Ġwann (Log fold change = ± 3, Supplementary Figure S7 ). Similarly, in San Ġwann vs. Imsida, Thiomicrorhabdus , Blautia , Staphylococcus , Commensalibacter , and Proteus were enriched in San Ġwann, while Acinetobacter was depleted (Log fold change = ± 3, Supplementary Figure S8 ). Finally, hornets sampled in the Qawra site showed an enrichment of more than 15 microbial genera, including Carnimonas, Arsenophonus, Frischella, Snodgrassella, Gilliamella , and Enterobacter , compared to hornets from San Ġwann and Gudja (Log fold change = ± 3.5, Supplementary Figure S9 and S10 ). 3.6 Effect of Diet on the Gut Microbial Community Weighted UniFrac (beta-diversity) analysis revealed a strong difference in gut microbiome composition between honey bee-feeding and cat food-scavenging hornets (PERMANOVA, p < 0.01). At the phylum level, Firmicutes were significantly more abundant in hornets consuming cat food (p < 0.05), while Proteobacteria were more prevalent in those feeding on honey bees (p < 0.05). At the family level, Morganellaceae was enriched in honey bee-feeding hornets (p < 0.01), whereas cat food-fed hornets exhibited a higher relative abundance of Spiroplasmataceae (p < 0.05). At the genus level, this trend was reflected in the higher relative abundance of Arsenophonus in honey bee-feeding hornets (p < 0.01) and Spiroplasma in cat food-feeding hornets (p < 0.05). Differential abundance analysis (DAA) further highlighted key microbial differences based on diet. Enterobacter was significantly more abundant in hornets consuming cat food, while Arsenophonus was enriched in honey bee-feeding hornets (Log fold change = ± 3, Supplementary Figure S11 ). Additionally, significant microbiome differences were detected between hornets scavenging cat food in Qawra and those in Imsida. Specifically, Arsenophonus , Gilliamella , Weissella , and Fructobacillus were more abundant in Qawra, whereas Planococcus , Salinimicrobium , and Snodgrassella were more prevalent in Imsida (Log fold change = ± 3). 3.7 Gut microbiome Total Bacteria and Pathogens Load qPCR results showed that the total bacteria absolute abundance varies between Log 6 and 9 among the single sampled hornets (Fig. 3 A). However, no significant differences were highlighted when the different sampling site were compared. Considering the pathogens load, N. ceranae was detected in the 97.15% of the sampled hornets (70 individuals), while Serratia ( luxS gene) and C. bombi frequency of positive detection was 71.43% and 62.86%, respectively. C. bombi exhibited the widest absolute abundance per hornet (Log 4.29 ± 3.58, Fig. 3 D) respect the other pathogens detected, followed by N. ceranae (Log 2.64 ± 0.75, Fig. 3 B) and Serratia (Log 1.17 ± 0.87, Fig. 3 C). When the sampling site were considered, no significant variations were highlighted in the hornets’ gut microbiome pathogens load for N. ceranae and C. bombi . Conversely, Serratia absolute abundance of the hornets sampled in Imsida (1.76 ± 0.81 luxS gene copies/gut) was higher than the individuals sampled in Gudja (0.99 ± 0.68 luxS gene copies/gut) and San Ġwann (0.71 ± 0.81 luxS gene copies/gut) Malta Island sites ( p < 0.05, Fig. 3 C). No positive hornets for the pathogens N. apis, N. bombi, C. mellificae, L. passim, A. bombi, Listeria , and Salmonella . were found. All the qPCR results are reported in Supplementary Table S4 . Discussion Composition of the Gut Microbiota in Vespa orientalis The gut microbiota of V. orientalis was dominated by Firmicutes and Proteobacteria, consistent with findings in previous studies on other Vespa species [ 19 – 21 , 36 ]. Additionally, Bacteroidetes and Actinobacteria were present, aligning with most prior studies, except for [ 36 ], who did not report these phyla. These results suggest a degree of conservation in the hornet gut microbiome at the phylum level, likely reflecting shared physiological traits and dietary habits across Vespa species. However, at lower taxonomic levels, significant variation was observed, reinforcing previous reports that gut composition diverges among Vespa species [ 19 ]. The most abundant genera in V. orientalis were Spiroplasma and Arsenophonus , with Spiroplasma having been reported in Vespa only in the recent study by [ 20 ]. Interestingly, Arsenophonus has not been previously documented in hornet gut microbiota. This suggests that some members of the microbiome may be species-specific or influenced by environmental conditions. The predominance of Arsenophonus in hornets from Gudja, which was also the most sampled location, raises the possibility of geographical or ecological factors shaping microbiota composition. Several other genera identified in this study, including Fructobacillus , Leuconostoc , Lactococcus , Weissella , Gilliamella , Carnimonas , Snodgrassella , and Pantoea , were also present in previous Vespa gut microbiome studies [ 19 ]. The detection of Gilliamella and Snodgrassella , which are core members of the honey bee microbiota, suggests a potential microbial exchange between hornets and their honey bee prey. Otherwise, our results designated that the main V. orientalis microbiome core family are Spiroplasmataceae, Morganellaceae, Halomonadaceae, Erwiniaceae, Burkholderiaceae, Moraxellaceae, Leuconostocaceae, and Microbacteriaceae. Specifically, V. orientalis core gut microbiome genus belonging to Carnimonas , Halomonas , Arsenophonus , Fructobacillus , Spiroplasma , Lactococcus , Acinetobacter , Rosenbergiella , Burkholderia , and Leifsonia . 4.2 Beekeeper Survey and Vespa orientalis Impact on Apiaries The beekeeper survey conducted between 2022 and 2024 provides valuable insights into the perceived impact of V. orientalis on honey bee colonies in Malta. Across all three years, 100% of responding beekeepers reported V. orientalis sightings, confirming its continued presence in Maltese apiaries. However, reported colony losses due to hornet predation fluctuated, with a peak in 2022 (63.8%), a decline in 2023 (29.4%), and a resurgence in 2024 (59.5%). This pattern suggests that 2023 was an anomalous year with reduced hornet activity, potentially influenced by external ecological factors. The decline in colony losses reported in 2023 could be attributed to several possible factors. One explanation is climatic variability, as beekeepers cited prolonged cold weather and food scarcity as potential stressors on hornet populations ( Appendix 1 ). A colder-than-usual season could have delayed hornet colony establishment, reducing predation pressure on honey bee colonies [ 37 ]. Human intervention, including trapping and manual removal efforts, was also reported as a potential factor, though declining beekeeper engagement in control measures over time suggests that this alone may not fully explain the observed trend. Furthermore, an increase in alternative protein sources in urban and peri-urban areas could have lessened the reliance of V. orientalis on honey bee predation, resulting in a temporary decline in impact. These possibilities highlight the need for further ecological monitoring to determine how climatic and environmental variables influence hornet population dynamics over time. Intervention efforts by beekeepers showed a general decline over the three-year period. In 2022, 82.8% of beekeepers reported taking action against V. orientalis , but this fell to 73.5% in 2023 and 75.7% in 2024. While slightly increasing again in 2024, this decline may indicate reduced beekeeper engagement, changes in hornet activity, or shifting perceptions of intervention effectiveness. The effectiveness of control strategies was also increasingly questioned, with only 43.2% of beekeepers in 2024 finding their interventions successful, down from 52.9% in 2023. The increasing failure of control efforts highlights the need to reassess integrated management strategies. The seasonal trend in honey bee losses supports the idea that V. orientalis exerts the highest predation pressure between July and October. This period corresponds with peak hornet foraging activity, likely driven by increased protein demands for colony development. The microbiome data from honey bee-fed hornets, particularly the enrichment of Arsenophonus , aligns with this trend, suggesting that microbial signatures in hornet gut communities could serve as indirect indicators of predation intensity. Future studies could explore whether microbiome analysis can complement traditional survey data in monitoring hornet foraging behaviours and their seasonal impacts on beekeeping. The seasonal trend in honey bee losses suggests that V. orientalis exerts its highest predation pressure between July and October, coinciding with peak foraging activity. This period likely reflects increased protein demands for colony development, as hornet larvae require protein-rich diets, which worker hornets obtain by hunting insects, including honey bees, or scavenging protein sources in urban waste. In contrast, adult hornets primarily consume carbohydrates, such as nectar, honeydew, and fruit, adapting their diet based on seasonal availability. Microbiome analysis of honey bee-fed hornets revealed enrichment of Arsenophonus , a bacterial genus associated with honey bee gut communities, further supporting the dietary shift from carbohydrate-rich to protein-based foraging. These microbial signatures in the hornet gut may serve as indirect indicators of predation intensity. As this study provides only a single time-point snapshot of the V. orientalis gut microbiota, longer-term research is needed to capture seasonal shifts. Earlier in the active season, when hornets rely more on carbohydrate sources, their microbiota may differ significantly from the profiles observed during peak predation. Future longitudinal studies could explore these dietary-driven microbiome changes, enhancing our understanding of hornet ecology, pathogen transmission risks, and the potential for microbiome analysis as a complementary tool for monitoring seasonal foraging behaviours and their impacts on beekeeping. 4.3 Diet as Driver of Microbial Variation Phylogenetic diversity (Faith PD) showed no significant difference between honey bee and cat food-feeding hornets. This suggests that despite potential dietary-driven compositional shifts, both groups maintained similar levels of microbial phylogenetic diversity. These findings align with [ 19 ], who reported comparable alpha diversity values between Vespa mandarinia and Vespa simillima , despite differences in diet. Suenami et al. [ 19 ] proposed that core OTUs in hornets are primarily diet-dependent rather than coevolved with the host, which may explain the similarity in gut diversity despite dietary differences. Similarly, the results of the alpha diversity metrics indicate that gut microbiota richness and evenness were comparable between hornets feeding on cat food and honey bees. No significant differences were detected in species richness (Observed Features) or evenness (Evenness), suggesting that food source did not influence overall microbial diversity. However, while not statistically significant, cat food-feeding hornets exhibited a trend toward lower evenness, indicating a potential dominance of specific bacterial taxa. This pattern was further supported by Differential Abundance Analysis (DAA), which identified several genera contributing to microbiota differences across food sources. Hornets feeding on cat food exhibited a significantly higher abundance of Enterobacter , while those feeding on honey bees had increased levels of Arsenophonus . This pattern aligns with findings from Section 4.4 , where hornets from Gudja, a natural apiary site, were enriched in Arsenophonus , while those from Imsida, an urban site, showed higher levels of Enterobacter . Enterobacter , a member of Enterobacteriaceae, is known to occur in raw meat and has been identified in spoiled pet food [ 38 , 39 ]. Its presence in cat food-feeding hornets suggests dietary transmission from scavenged protein-rich food sources. Enterobacter has been previously detected in other insects, including tsetse flies and fruit flies [ 40 , 41 ] and was also reported in Vespula germanica wasp stings [ 42 ]. The potential pathogenicity of Enterobacter in hornets warrants further investigation. Interestingly, some honey bee-associated bacteria, such as Gilliamella , Snodgrassella , and Bifidobacterium , did not show significant abundance differences between the two food sources. Previous studies on Vespa species linked the presence of Gilliamella to honey bee predation [ 36 ]. The lack of a significant difference in this study could suggest that these microbes may not be strictly diet-dependent in V. orientalis . Alternatively, this pattern could be explained by Malta’s relatively small geographic scale and the short distances between sites, allowing hornets from urban areas to visit apiaries before being sampled. Although research on the flight range of V. orientalis is limited, studies on Vespa velutina (Asian hornet) suggest that workers can forage up to around 1km from their nests [ 43 ]. Given the behavioural and ecological similarities among hornet species, it is plausible that V. orientalis exhibits comparable foraging distances, allowing individuals to easily move between urban and beekeeping environments. This mobility could explain the presence of honey bee-associated microbes in hornets sampled from urban sites, supporting the possibility of microbial exchange across different foraging habitats. 4.4 Geographic Variation and Environmental Influence on Microbiota In addition to diet, site-based differences were notable, particularly in Gudja vs. Imsida comparisons. Hornets from Gudja showed enrichment in Arsenophonus , while those from Imsida had higher levels of Hafnia-Obesumbacterium, Serratia , and Enterobacter —all of which are associated with raw meat spoilage [ 38 , 44 ]. This further supports the idea that diet is a key driver of microbiota composition. Arsenophonus , on the other hand, is a well-documented insect-associated symbiont, with roles ranging from male-killing in some hosts to nutritional mutualism [ 45 , 46 ]. It has been identified in honey bees, where it was initially mistaken for the pathogen Arsenophonus nasoniae but later confirmed as a unique strain ( A. apicola ) [ 47 ]. Arsenophonus has previously been identified in honey bee colonies, where it was associated with poor colony health [ 48 ]. The detection of Arsenophonus in hornets feeding on honey bees indicates that predation may facilitate microbial transfer between predator and prey, potentially influencing pathogen dynamics within apiaries. These findings highlight that diet significantly shapes V. orientalis ' microbiome, possibly through differences in nutrient composition, exposure to gut microbiota from prey, and environmental microbial sources. Beta diversity analysis revealed clustering patterns in microbial composition based on food source and location. Bray-Curtis dissimilarity indicated some degree of separation between groups. The Unweighted UniFrac analysis showed no significant differences in microbial presence/absence, suggesting that rare taxa did not drive the observed variation. However, Weighted UniFrac analysis revealed significant differences between honey bee-feeding and cat food-feeding hornets, highlighting that taxonomic abundance was a key factor in gut microbiota differences. Our results suggest that location might play a role in microbial composition, as indicated by the significant differences in Weighted UniFrac distances between Gudja and Imsida, as well as Gudja and San Ġwann. Gudja samples exhibited a distinct microbial community compared to other sites, even when compared to San Ġwann, which was also a honey bee-feeding site. These findings are consistent with previous studies suggesting that geographical location (and not just diet) can shape gut microbiota composition. The observed microbial differences between Gudja and the other study sites may reflect differences in environmental resource availability, such as floral resources, host genetics, prey abundance and prey microbiota, or human-associated food sources. This highlights the importance of landscape composition in shaping hornet gut microbiota, warranting further study into how urban or peri-urban vs. rural environments influence microbial acquisition patterns. 4.5 Spillover vs. Spillback: Rethinking V. orientalis ' Role in Pathogen Dynamics The role of Vespa orientalis as a pathogen reservoir rather than a primary spillover vector mirrors patterns observed in invasive species. A similar dynamic has been documented in Callosciurus erythraeus , an invasive squirrel in Japan, which has been shown to amplify local parasite burdens by acting as an additional host for both native and exotic ectoparasites [ 49 ]. This process, known as spillback, occurs when an invasive species does not introduce new pathogens but instead facilitates their persistence and circulation within an ecosystem [ 50 , 51 ]. By serving as additional hosts, invasive organisms can disrupt the balance between native species and pathogens, increasing infection risks. While hornets have previously been considered vectors capable of transmitting pathogens to honey bees (spillover) [ 24 , 52 , 53 ] our findings suggest a possible alternative spillback scenario, whereby a pathogen is transmitted from a new host species ( V. orientalis ) back to its original host or ecosystem, potentially altering infection patterns or pathogen prevalence. Despite its ecological significance, spillback remains underexplored, partly due to the difficulty of establishing pathogen transmission directionality. The stochastic presence of pathogens and viruses reported by [ 5 ] supports the hypothesis that hornets do not naturally harbour these pathogens but rather acquire them from the environment or prey, indicating that hornets likely act as pathogen reservoirs and contribute to a spillback dynamic. Environmental factors such as increasing urbanisation, climate change, and resource availability may further shape microbial spillback dynamics, altering pathogen transmission risks between hornets, honey bees, other insects and humans. Understanding how these landscape-level changes influence the gut microbiome of V. orientalis can provide deeper insights into the broader socioecological consequences of invasive species, particularly within a One Health framework. Our findings confirm that V. orientalis harbours Nosema ceranae and Crithidia bombi , both of which were detected in a large proportion of sampled hornets and have been previously reported in this species [ 53 , 54 ]. These results suggest a potential spillback mechanism, though further research is needed to confirm whether V. orientalis plays an active role in pathogen transmission. The detection of bee-specific pathogens in honey bee-feeding hornets suggests that hornets may acquire these pathogens directly from their prey, reinforcing their role as pathogen sinks rather than primary reservoirs. However, the persistence of these microbes within the hornet gut and the potential for secondary transmission remain uncertain. Research on other predator insects has shown that some microbial species can survive passage through the gut and may be excreted in a viable form (e.g., in faeces or regurgitation), which could provide an indirect transmission pathway back to honey bees or the environment [ 55 ]. Further studies are needed to assess the viability of Nosema ceranae and Crithidia bombi post-digestion and determine whether hornets contribute to pathogen cycling in apiary environments. This is particularly relevant for pollinator health and ecosystem stability, two key pillars of the One Health approach. The dietary-driven microbial shifts in V. orientalis , such as the enrichment of Arsenophonus in honey bee-fed individuals and Enterobacter in cat food-scavenging hornets, closely parallel observations in C. erythraeus , where diet influenced the prevalence of different bacterial taxa. Additionally, both studies highlight significant spatial variation in microbial loads, suggesting that local environmental conditions may shape pathogen spillback risks. While this suggests a strong predator-prey microbial exchange, the one-way nature of this transfer remains to be fully established. Some microbial taxa, such as Arsenophonus , have been identified as endosymbionts in honey bees [ 56 ], yet their functional role in hornets is still unclear. If Arsenophonus can persist and proliferate within V. orientalis , it may challenge the notion that hornets strictly function as microbial sinks rather than as potential secondary hosts or facilitators of microbial exchange. The detection of Crithidia bombi in V. orientalis may also suggest a broader dietary range than previously documented. While hornets are known to primarily prey on honey bees, the presence of C. bombi , a pathogen typically associated with bumble bees, raises the possibility that V. orientalis may also prey on or scavenge from Bombus species or other solitary bees as is known with other Vespa species such as Vespa velutina nigrithorax [ 57 ]. This could have significant ecological implications, as bumble bees are essential pollinators, and increased predation pressure from V. orientalis could exacerbate population declines in wild pollinators. Alternatively, hornets might acquire C. bombi indirectly through floral contamination, as C. bombi can persist on flowers and be transmitted via shared foraging sites [ 58 ]. Further research is needed to determine whether V. orientalis actively preys on bumble bees or acquires C. bombi through environmental exposure, and what implications this may have for pollinator pathogen dynamics. The gut microbiota of V. orientalis revealed clear dietary influences, with enrichment of Arsenophonus in honey bee-feeding hornets and Enterobacter in those scavenging on cat food. These findings strongly indicate a microbial exchange between predator and prey rather than V. orientalis acting as a primary pathogen reservoir for honey bees. The predatory behaviour of hornets involves immediate and lethal interactions, making microbial acquisition from honey bees a likely one-way transfer. However, potential secondary transmission routes, such as environmental shedding, faecal deposition, or regurgitation, remain unexamined and warrant further study. 4.6 Pathogen Detection and One Health Implications Our qPCR-based pathogen screening primarily targeted bee-associated microbes. Of the eight tested pathogens, only Nosema ceranae , Serratia , and Crithidia bombi were detected, with Serratia exhibiting low abundance. The presence of Serratia in V. orientalis suggests potential exposure to human-associated environments, such as urban waste or agricultural runoff. Serratia species are opportunistic pathogens with relevance to both insect and human health. Given that hornets frequently scavenge in human-dominated habitats, their potential role in maintaining environmental reservoirs of foodborne or antimicrobial-resistant bacteria cannot be overlooked. We also screened for two human pathogens, Listeria and Salmonella , both of which tested negative in all samples, consistent with findings by Zucca et al., [ 5 ]. This suggests that V. orientalis may not serve as a primary carrier of these pathogens. However, broader screening across different geographic regions and dietary contexts is necessary to fully evaluate potential public health risks. Integrating a One Health perspective, future research should evaluate whether V. orientalis contributes to pathogen spillover or spillback dynamics within apiaries, urban environments, and broader ecosystems. The intersection of ecological, veterinary, and public health considerations will be essential in formulating evidence-based management strategies that mitigate risks associated with V. orientalis in both native and invaded habitats. Conclusion This study provides the first comprehensive characterisation of the gut microbiota of Vespa orientalis , revealing its dynamic composition influenced by both environmental factors and diet. While the gut microbiota at the phylum level aligns with previous research on other Vespa species, significant differences at the family and genus levels highlight the species-specific and habitat-driven nature of microbial communities. Our findings demonstrate that V. orientalis exhibits distinct microbiota compositions across different landscapes, suggesting that microbial plasticity may contribute to its resilience in both urban and natural environments. The pronounced enrichment of Enterobacter in hornets scavenging on cat food and Arsenophonus in honey bee-feeding individuals underscores the role of diet in shaping microbial diversity. This suggests that urban scavenging behaviours could alter gut microbial balance, while honey bee predation may facilitate microbial exchange between predator and prey. The presence of bee-associated microbes in V. orientalis further supports a spillback dynamic rather than a direct spillover effect, indicating that the hornet primarily functions as a microbial reservoir rather than an active pathogen vector. These insights into V. orientalis microbiota and its potential interactions with honey bee pathogens contribute to a broader understanding of the ecological and epidemiological implications of this species. Future research should explore seasonal shifts in gut microbiota, the viability of pathogen transmission, and the potential consequences of microbial exchange within apiary environments. Integrating these findings into One Health frameworks could support the development of targeted management strategies and even open new avenues for biological control, such as microbial-based interventions to regulate V. orientalis populations, ultimately mitigating its impact on pollinators, ecosystems, and public health. Declarations Competing Interests The authors declare no conflict of interests. Ethics approval Ethical review and approval were waived, because the Italian law does not require and ethical approval for tests performed on arthropods with exceptions of cephalopods according to the Italian D.L. 4 March 2014 n. 26, and Italian implementing decree following the European regulation 2010/63/UE. Authors Contribution please add any other contribution type or any contributor. D.M and S.C. were involved in the experimental design; S.C., M.M., and C.B. in formal NGS and qPCR analysis; L.B. performed bioinformatic analysis; D.A, S.C and C.B were involved in statistical analysis and data curation; J.S. carried out the V. orientalis impact survey; D.A. and D.D.G. coordinated the research work; S.C and C.B wrote the manuscript; D.A., D.M., L.B., and D.D.G., revised the manuscript. D.A., S.C., D.M., and D.D.G., were involved in funding acquisition. Data availability statement NGS raw sequence data have been submitted to NCBI repository under the Sequence Read Archive (SRA) databases under the Bioproject N° PRJNA1232968, biosamples SAMN47255446 - SAMN47255585. Funding This study received the financial support from the Tertiary Education Scholarships Scheme by the Ministry for Education, Sport, Youth, Research and Innovation in Malta (TESS 2022). 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6179679","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":444456723,"identity":"30d633ee-8f81-46c5-9ff8-5fc4b0add4eb","order_by":0,"name":"Simone Cutajar","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Simone","middleName":"","lastName":"Cutajar","suffix":""},{"id":444456725,"identity":"6de03534-146b-4780-a24f-5de44f58bdfb","order_by":1,"name":"Chiara Braglia","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Chiara","middleName":"","lastName":"Braglia","suffix":""},{"id":444456727,"identity":"70dc24e1-497b-4584-8997-7b845587623e","order_by":2,"name":"Daniele Alberoni","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA/klEQVRIie2QsWrDMBBAFTJkucSrBCH9hQsGdwn1rwQCndzgUaNLIV3a3Z8jcUMWlawesgUyZUjp0kKhPRUPhSJl7aCHOE5CT3cnIRKJ/4jxq+ZkBD97yDiQT+IKcjLsFdX0StAxPvxSBPLJUETKTLYv1pxxIbKHsT1ovZ/m3Z2lWotpGVCUWy9ti7dC0mQ1d+4IRbdeUuvCjaGpkAC5eYJC3W84dnwy3kSU3QnpE7/EFcH1h1fy9pLi3/Qjc61i4BWUFxTVndA+4QrmPItqHIF0XLd1EsAEfmxX5ed3fTObbZ/ta6OpzB6r/K3Wi3LUBMr0/OlCxu8nEolEIso3AdlY7gwYF5wAAAAASUVORK5CYII=","orcid":"","institution":"University of Bologna","correspondingAuthor":true,"prefix":"","firstName":"Daniele","middleName":"","lastName":"Alberoni","suffix":""},{"id":444456728,"identity":"13a5244b-36f3-4881-98d1-0e4ddf0d22e9","order_by":3,"name":"Martina Mifsud","email":"","orcid":"","institution":"L-Università tà Malta","correspondingAuthor":false,"prefix":"","firstName":"Martina","middleName":"","lastName":"Mifsud","suffix":""},{"id":444456729,"identity":"108560c7-09ae-4c39-90ec-490cdc6a8363","order_by":4,"name":"Loredana Baffoni","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Loredana","middleName":"","lastName":"Baffoni","suffix":""},{"id":444456730,"identity":"36f441b9-8dd1-44fd-a91b-ce1c15cf69ed","order_by":5,"name":"Jorge Spiteri","email":"","orcid":"","institution":"Malta Beekeepers’ Association","correspondingAuthor":false,"prefix":"","firstName":"Jorge","middleName":"","lastName":"Spiteri","suffix":""},{"id":444456731,"identity":"a31a22f7-a09e-405b-8e03-d68b4b6d6906","order_by":6,"name":"Diana Di Gioia","email":"","orcid":"","institution":"University of Bologna","correspondingAuthor":false,"prefix":"","firstName":"Diana","middleName":"Di","lastName":"Gioia","suffix":""},{"id":444456732,"identity":"7eb9378c-3982-4e22-87bf-b6ffc0acb465","order_by":7,"name":"David Mifsud","email":"","orcid":"","institution":"L-Università tà Malta","correspondingAuthor":false,"prefix":"","firstName":"David","middleName":"","lastName":"Mifsud","suffix":""}],"badges":[],"createdAt":"2025-03-07 16:08:19","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-6179679/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-6179679/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":81138583,"identity":"63e282ce-9640-4439-bafc-94bf7f8252ac","added_by":"auto","created_at":"2025-04-22 16:12:58","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":3459467,"visible":true,"origin":"","legend":"\u003cp\u003eRelative abundance of the bacterial gut microbiota of \u003cem\u003eV. orientalis \u003c/em\u003eat family and genus level. Genera that had a relative abundance of less than 1% in all samples were labelled as ‘Other’.\u003c/p\u003e","description":"","filename":"Fig1CoreGenerainVespaorientalis.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6179679/v1/617348a7a06e7162ad6c47ed.jpg"},{"id":81138935,"identity":"f8e5f621-6e2c-4c95-893d-30b27266370f","added_by":"auto","created_at":"2025-04-22 16:20:58","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":2233497,"visible":true,"origin":"","legend":"\u003cp\u003eScatter plot illustrating the prevalence and mean relative abundance of bacterial genera within the \u003cem\u003eV. orientalis\u003c/em\u003e gut microbiota. Each point represents a genus, positioned according to its frequency across samples (prevalence) and its average proportion (abundance). The red dashed lines mark the chosen cut off for both parameters, while the taxa marked in red represent the core microbiome of \u003cem\u003eV. orientalis.\u003c/em\u003e\u003c/p\u003e","description":"","filename":"Fig2Prevalencevs.AbundanceinVespaOrientalisGenera.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6179679/v1/090485675e4fb10686e626a0.jpg"},{"id":81138580,"identity":"1c37440d-11fc-4fff-a99d-90379c353241","added_by":"auto","created_at":"2025-04-22 16:12:58","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":1567743,"visible":true,"origin":"","legend":"\u003cp\u003eqPCR results on A) total bacteria, B) \u003cem\u003eN. ceranae \u003c/em\u003epathogen, C) \u003cem\u003eSerratia\u003c/em\u003e pathogen, and D) \u003cem\u003eC. bombi\u003c/em\u003e detected in the \u003cem\u003eV. orientalis\u003c/em\u003e gut microbiome sampled in the different Maltese sites. Different letters on the top of the boxplot indicate a \u003cem\u003ep\u003c/em\u003e\u0026lt;0.05.\u003c/p\u003e","description":"","filename":"Fig3PathogensandEubacteria.jpg","url":"https://assets-eu.researchsquare.com/files/rs-6179679/v1/3dfef165feee5d21166a0ca1.jpg"},{"id":81519877,"identity":"0e7c0d2a-33b3-4116-9dab-6cd2d2e06c75","added_by":"auto","created_at":"2025-04-28 07:54:09","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":8526194,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6179679/v1/3b9fd075-3e1f-4757-89cd-dda81c42f034.pdf"},{"id":81138585,"identity":"d498f1ef-9ebe-4086-a461-c74c5afee12a","added_by":"auto","created_at":"2025-04-22 16:12:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"supplement","size":1668136,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementarymaterialsCutajar2025.pdf","url":"https://assets-eu.researchsquare.com/files/rs-6179679/v1/d89f2bc34c41b7302b6b1e2d.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Rethinking spillover risks: first description of the Vespa orientalis gut microbiome and its impact on honeybee and human health","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cem\u003eVespa orientalis\u003c/em\u003e, commonly known as the Oriental hornet, is a large eusocial insect belonging to the Vespidae family. It is native to the southeastern Mediterranean region, including Malta, southern Italy, Cyprus, as well as northeastern and eastern Africa, the Middle East, and Central Asia [\u003cspan additionalcitationids=\"CR2\" citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. This species has gained attention for its expanding range, via accidental human-assisted introductions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e], and its ecological impact, particularly its interactions with honey bee populations [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. \u003cem\u003eV. orientalis\u003c/em\u003e typically establishes colonies in underground nests and preys on honey bees and other insects, raising concern among beekeepers [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. In addition to posing a threat to beekeeping and native biodiversity, \u003cem\u003eV. orientalis\u003c/em\u003e may also impact public health. As an opportunistic feeder, this hornet regularly comes into contact with raw or decaying proteins (e.g., meat, cat food), as well as sugar-rich materials (e.g., fruits, honey) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. These diverse feeding behaviours make \u003cem\u003eV. orientalis\u003c/em\u003e a frequent presence in urban and peri-urban environments [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e, \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Because they often forage in close proximity to human activities, there is an increased likelihood of harbouring and transmitting microbes relevant to human health.\u003c/p\u003e \u003cp\u003eTo date, \u003cem\u003eV. orientalis\u003c/em\u003e has been reported in numerous non-native regions, including previously uncolonised areas of Europe, as well as South America (Brazil and Chile) [\u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e], and North America (Mexico) [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. In Europe, it was first recorded in Spain in 2012, where it is now considered established [\u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e11\u003c/span\u003e, \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. Subsequent detections have been reported in Romania [\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e], France [\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], northern Italy [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e] and the Greek islands [\u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e]. This broad distribution across distant regions suggests that \u003cem\u003eV. orientalis\u003c/em\u003e possesses biological traits that enhance its invasion potential [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. In Malta, where \u003cem\u003eV. orientalis\u003c/em\u003e is considered indigenous, its adverse impact on apiculture has increased in recent years (\u003cb\u003eSurvey Appendix 1\u003c/b\u003e), alongside an extended period of activity [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. This increased predation on honey bees, which, in severe cases, can lead to entire colony collapse [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e], has raised concerns that \u003cem\u003eV. orientalis\u003c/em\u003e is exhibiting invasive behaviour in its native range. Its presence threatens pollination services, biodiversity, agricultural productivity, and apiculture.\u003c/p\u003e \u003cp\u003eThe recent spread and increased impact of \u003cem\u003eV. orientalis\u003c/em\u003e, even in its native range, have been linked to climate change, human-mediated dispersal, ecological shifts, urbanisation, and weakened honey bee colonies. Rising temperatures and milder winters enhance queen survival [\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e], while global trade facilitates unintentional introductions [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Urbanisation creates new nesting sites, and weakened honey bee colonies, affected by pesticides, habitat loss, and diseases, become more vulnerable to predation. These factors, combined with high propagule pressure, adaptability to human-altered environments, and human-assisted dispersal, allow \u003cem\u003eV. orientalis\u003c/em\u003e to establish in new ecological niches, posing a growing threat to local ecosystems [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRecent studies have highlighted the fundamental role of the gut microbiome in social insects, influencing health, nutrition, immunity, and adaptability [\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. While research has explored the microbiomes of hornet species such as \u003cem\u003eVespa mandarinia, Vespa simillima\u003c/em\u003e [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] and \u003cem\u003eVespa velutina\u003c/em\u003e with its subspecies \u003cem\u003eV. velutina\u003c/em\u003e subsp. \u003cem\u003enigrithorax\u003c/em\u003e and \u003cem\u003eV. velutina\u003c/em\u003e subsp. \u003cem\u003eauraria\u003c/em\u003e [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e, \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e]; no published studies have characterised the gut microbiota of \u003cem\u003eV. orientalis\u003c/em\u003e. Increasingly, studies on other social insects have shown that gut microbiota is strongly influenced by environmental factors and diet, shaping their adaptability and ecological interactions [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e23\u003c/span\u003e]. Understanding these microbial communities is particularly important in a species with global invasive potential, as it poses risks both as a honey bee predator and as a potential pathogen reservoir for honey bees and humans [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eBy analysing hornets from four sites in Malta, including individuals feeding on honey bees near apiaries and scavenging on cat food in urban and peri-urban habitats, this study aims to characterise the gut microbiota and potential pathogens of \u003cem\u003eV. orientalis\u003c/em\u003e, while distinguishing the effects of diet and environment on microbiome composition. Given its expanding range, evaluating \u003cem\u003eV. orientalis\u003c/em\u003e's potential health risks is of growing concern, particularly in the context of pathogen transmission to honey bees, other insects, and even humans. A One Health approach, which integrates the interconnected health of pollinators, ecosystems, and public health, provides a broader framework for assessing these risks. Since \u003cem\u003eV. orientalis\u003c/em\u003e may facilitate microbial exchanges across species, studying its gut microbiota could reveal pathogen transmission pathways and contribute to sustainable management strategies, including the development of microbial-based biological control methods.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Beekeeper Survey Data Collection\u003c/h2\u003e \u003cp\u003eTo assess the perceived impact of \u003cem\u003eV. orientalis\u003c/em\u003e on beekeeping in Malta, survey data were collected by the Malta Beekeeping Association (MBKA, VO 1527) from 2022 to 2024. The surveys aimed to document beekeeper-reported observations, colony and brood losses, mitigation efforts, and the effectiveness of control measures. The dataset was compiled from voluntary responses by MBKA members, representing a longitudinal perspective on the species' effects on apiculture in Malta. The survey provides insights into yearly variations in \u003cem\u003eV. orientalis\u003c/em\u003e apicultural impact and beekeeper interventions. Each annual survey contained a structured set of questions designed to capture key trends, such as reported colony losses attributed to hornet predation, and beekeeper interventions to mitigate the threat. While the questionnaire evolved slightly over the three-year period, core questions remained consistent to allow for comparative analysis. The responses were compiled, anonymised, and provided by the MBKA for integration into this study. The surveys were conducted in Maltese and subsequently translated into English by the study authors to ensure consistency and clarity in data interpretation. Survey results were analysed to detect changes in hornet impact over time and assess the effectiveness of control measures.\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2.1 Samples Collection\u003c/h3\u003e\n\u003cp\u003eAdult \u003cem\u003eV. orientalis\u003c/em\u003e individuals (\u003cb\u003eFigure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e, and \u003cb\u003eSupplementary Appendix 2\u003c/b\u003e) were collected from four site types categorised by dominant food source: ‘honey bee’ sites (locations with active apiaries) and ‘cat food’ sites (urban locations where hornets scavenging pet food). Sampling was conducted between September and October 2023 at four localities; an urban site in Imsida (VoU, University of Malta campus – 35°54'01\"N 14°28'59\"E), a peri-urban site in Qawra (VoQ – 35°56'50\"N 14°25'19\"E), a peri-urban San Ġwann site (VoS – 35°54'26.6\"N 14°27'49.3\"E), and a natural site in Gudja (VoG – 35°51'18\"N 14°30'35\"E). In each site (\u003cb\u003eFigure S2\u003c/b\u003e), hornets were captured randomly using a sweep net or an electric fly swatter, for a total of 70 samples. Specimens were placed on ice immediately after collection and transported to the University of Malta, where they were stored at − 80°C. They were then shipped frozen to the University of Bologna for molecular analysis.\u003c/p\u003e\n\u003ch3\u003e2.2 DNA Extraction\u003c/h3\u003e\n\u003cp\u003ePrior to DNA extraction, adult hornets were dissected at controlled temperature near 0°C, by using ethanol-sterilised forceps. The last abdominal segment was carefully removed along with the entire gut and transferred into a sterile 1.5 mL Eppendorf tube. A total of 70 gut samples were processed for microbial DNA extraction according to [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e]. DNA was extracted using the PureLink™ Genomic DNA Mini Kit (Thermo Fisher Scientific), following the manufacturer’s protocol. The extracted DNA was quantified using a Qubit dsDNA HS Assay Broad Range Kit (Thermo Fisher Scientific).\u003c/p\u003e\n\u003ch3\u003e2.3 Library Preparation and Sequencing\u003c/h3\u003e\n\u003cp\u003eLibrary preparation and sequencing were performed by IGA Technology Services S.r.l. (Udine, Italy). The 16S rRNA V3-V4 region was targeted for amplicon sequencing, using Illumina MiSeq technology. Each sample was sequenced with a target depth of 50,000 reads per sample. The sequencing service included PCR amplification, library preparation, and quality control (QC) checkpoints. Samples were directly processed through PCR amplification, and only successfully amplified libraries were used for sequencing. The sequencing platform was optimised to ensure a minimum of 95% of the target sequencing output (expressed in millions of reads).\u003c/p\u003e\n\u003ch3\u003e2.4 Quantitative Polymerase Chain Reaction (qPCR)\u003c/h3\u003e\n\u003cp\u003eThe absolute quantification of bee pathogens (\u003cem\u003eNosema ceranae\u003c/em\u003e, \u003cem\u003eN. apis\u003c/em\u003e, \u003cem\u003eN. bombi\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, \u003cem\u003eCrithidia bombi\u003c/em\u003e, \u003cem\u003eC. mellificae\u003c/em\u003e, \u003cem\u003eLotmaria passim\u003c/em\u003e, \u003cem\u003eApicystis bombi\u003c/em\u003e), human pathogens (\u003cem\u003eListeria\u003c/em\u003e and \u003cem\u003eSalmonella\u003c/em\u003e), and total bacteria were quantified with specific primers listed in \u003cb\u003eSupplementary Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e\u003c/b\u003e. The PCR products for each target were purified with NucleoSpin® Gel and PCR Clean-up (Macherey-Nagel), quantified with Qubit dsDNA Broad Range kit (Thermo Fisher Scientific) and converted in total amount of copies per microliter. Purified PCR products were used to generate standard curve-based quantification, obtained with serial dilution of the pre-amplified target amplicons (10\u003csup\u003e4\u003c/sup\u003e to 10\u003csup\u003e8\u003c/sup\u003e copies). Quantitative PCR protocols were carried out with QuantStudio® 5 Real-Time PCR System (Applied Biosystems), according to [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e]. Amplifications of each microbial target were carried out using PowerUp SYBR Green Master Mix (Applied Biosystems) in a final volume of 10 µL. Data were converted according to the respective rRNA copy number to obtain the absolute quantification of targeted microorganisms expressed in Log spores/gut for \u003cem\u003eNosema\u003c/em\u003e, Log cells/gut for \u003cem\u003eC. bombi\u003c/em\u003e, Log \u003cem\u003eluxS\u003c/em\u003e gene copies/gut for \u003cem\u003eSerratia\u003c/em\u003e, and Log 16S rRNA copies/gut for the total bacteria.\u003c/p\u003e \u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Bioinformatics\u003c/h2\u003e \u003cp\u003eRaw sequencing reads were processed using QIIME2-amplicon-2024.2 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e]. After importing data we eliminated samples with sequences less than 100,000 reads. The DADA2 plugin was used for read joining, denoising, and chimera filtering. Taxonomic classification was performed using the Silva 138.1 database [\u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e] with the plugin \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eqiime feature-classifier\u003c/span\u003e using vsearch \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003e(classify-consensus-vsearch)\u003c/span\u003e, employing a full-length sequence classifier. Before visualization using \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eqiime taxa barplot,\u003c/span\u003e taxonomic assignment and representative sequences were filtered for “Mitochondria”, “Chloroplast”, and “Unassigned” using plugin \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eqiime taxa\u003c/span\u003e and the methods \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003efilter-table\u003c/span\u003e and \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003efilter-seqs\u003c/span\u003e. Phylogenetic relationships were inferred by constructing a rooted tree using \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eqiime phylogeny align-to-tree-mafft-fasttree\u003c/span\u003e. Alpha and beta diversity analyses were conducted using this rooted tree and 16710 as sampling-depth. Rarefaction curves were generated with \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eqiime diversity\u003c/span\u003e plugin and the visualizer \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003ealpha-rarefaction\u003c/span\u003e .\u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003e2.5 Core Microbiota Determination\u003c/h3\u003e\n\u003cp\u003eTo identify the core gut microbiota of \u003cem\u003eVespa orientalis\u003c/em\u003e, bacterial taxa consistently present across samples at a predefined prevalence threshold were considered. Microbial presence was assessed at the Amplicon Sequence Variant (ASV) level, and prevalence (%) was calculated as (\u003cem\u003enumber of samples where the taxon is present\u003c/em\u003e / \u003cem\u003etotal number of samples\u003c/em\u003e) × 100. In this study, core gut microbiota was defined as taxa detected in at least 80% of samples (across all locations) with a relative abundance greater than 1%, following established thresholds [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e, \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e30\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003e2.6 Statistical Analysis\u003c/h3\u003e\n\u003cp\u003eAll statistical analyses were conducted using QIIME2-amplicon-2024.2 [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] and R version 4.3.3 (R foundation for Statistical Computing; Vienna, Austria) to assess microbial diversity and composition across different food sources and geographic locations. Alpha diversity was assessed to evaluate microbial richness and evenness within samples using three indices: (i) Faith’s Phylogenetic Diversity (Faith PD), which accounts for evolutionary relationships between taxa; (ii) Observed Features, representing the number of unique bacterial taxa per sample; and (iii) Pielou’s Evenness, which quantifies the uniformity of taxa distribution within a sample. Differences in alpha diversity between groups were assessed using the Mann-Whitney U test, a non-parametric approach suitable for comparing microbial diversity across independent groups. To account for multiple comparisons, Bonferroni correction was applied. To examine differences in microbiota composition among sites and diets, beta diversity was analysed using both Weighted and Unweighted UniFrac distances, which consider both phylogenetic relationships and relative abundances of bacterial taxa. PERMANOVA (Permutational Multivariate Analysis of Variance) with 999 permutations was used to determine whether microbial community composition varied significantly between groups. Beta diversity patterns were visualized through Principal Coordinates Analysis (PCoA) and non-metric multidimensional scaling (NMDS) based on Bray-Curtis dissimilarity. Differential abundance analysis was performed using plugin \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eqiime composition,\u003c/span\u003e the method \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eancombc\u003c/span\u003e and the visualizer \u003cspan fontcategory=\"NonProportional\" class=\"\" name=\"Emphasis\"\u003eda-barplot\u003c/span\u003e to show bacterial taxa that were enriched in different groups. This method was selected for its ability to account for compositional data biases while providing robust estimates of differential abundance. A log fold change (LFC) threshold of ± 1.5 was applied to define relevant differences. Finally, to compare the relative abundance from NGS data and the absolute abundance of total bacteria, and the honey bee and human pathogens from qPCR data, one-way ANOVA with Tukey HSD [\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] post-hoc test was applied for normally distributed data with homoscedasticity. On the other hand, Kruskal–Wallis one-way ANOVA with Dunn’s multiple comparisons post-hoc test was used for non-normal distributed data [\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e, \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e]. Shapiro-Wilk [\u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] test and Levene test [\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] were used to assess data distribution and homoscedasticity. All statistical analyses were conducted at a significance threshold of \u003cem\u003ep\u003c/em\u003e ≤ 0.05, with appropriate corrections applied for multiple comparisons.\u003c/p\u003e \u003c/div\u003e "},{"header":"Results","content":"\u003ch2\u003e3.1 Beekeeper Survey Results\u003c/h2\u003e\u003cp\u003eThe beekeeper survey data collected from 2022 to 2024 provide insights into the perceived impact of \u003cem\u003eV. orientalis\u003c/em\u003e on apiculture in Malta. A total of 58 beekeepers responded in 2022, 34 in 2023, and 37 in 2024, allowing for a comparative analysis of trends over time. In each survey year, all responding beekeepers (100%) reported \u003cem\u003eV. orientalis\u003c/em\u003e sightings in their apiaries. Reported colony losses due to hornet predation followed a similar pattern, with 37 cases in 2022 (63.8% of respondents), dropping to 10 in 2023 (29.4%), and rising again to 22 in 2024 (59.5%). The decline in 2023 suggests a temporary reduction in hornet impact, though losses rebounded the following year. Beekeepers reported various intervention efforts to control \u003cem\u003eV. orientalis\u003c/em\u003e, including trapping of queens and/or drones and manual removal. In 2022, 48 beekeepers (82.8%) took action against the hornet, decreasing to 25 (73.5%) in 2023 and 28 (75.7%) in 2024. This decline in intervention rates may indicate reduced beekeeper engagement or shifts in hornet population dynamics. Assessments of intervention effectiveness varied. In 2023, 18 beekeepers (52.9%) considered their efforts effective, while four (11.8%) reported complete failure. By 2024, the number of beekeepers who found interventions successful dropped to 16 (43.2%), while those reporting failed control measures increased to seven (18.9%). This suggests that traditional mitigation strategies may be losing efficacy over time. Overall, these survey findings suggest that although \u003cem\u003eV. orientalis\u003c/em\u003e sightings have remained consistently high, colony losses persisted, and beekeeper interventions became less frequent and less effective. The pronounced reduction in colony losses in 2023 appears to have been short-lived, as evidenced by the resurgence in 2024. The increase in failed interventions in 2024 raises concerns about the growing impact of \u003cem\u003eV. orientalis\u003c/em\u003e on beekeeping in Malta.\u003c/p\u003e\u003ch2\u003e3.2 Next-Generation Sequencing (NGS) Output Results\u003c/h2\u003e\u003cp\u003eHigh-throughput sequencing of \u003cem\u003eV. orientalis\u003c/em\u003e gut samples generated a total of 2,964,602 clean paired reads, ranging from 16,710 to 83,316 paired reads per sample. Microbial community analysis using QIIME2-amplicon-2024.2 identified 7,309 Amplicon Sequence Variants (ASVs). To ensure uniform comparisons across samples, all data were subsampled to the study’s minimum sequencing depth (50,000 reads), a threshold expected to have minimal impact on downstream analyses. This led to the exclusion of five samples (VoGB6, VoGBa2, VoGB10, VoGB19, and VoGB3).\u003c/p\u003e\u003cp\u003e \u003cb\u003e3.3 Microbial Community Composition in\u003c/b\u003e \u003cb\u003eVespa orientalis\u003c/b\u003e\u003c/p\u003e\u003cp\u003ePhylogenetic classification revealed that the gut microbiota of \u003cem\u003eV. orientalis\u003c/em\u003e was predominantly composed of Firmicutes (71.8% relative abundance), followed by Proteobacteria (22.2%), Actinobacteriota (1.91%), Bacteroidota (0.70%), and Cyanobacteria (0.41%). Other phyla collectively accounted for less than 9.68% of the total relative abundance. At the family level, the most dominant taxa were Spiroplasmataceae (67.05%), Morganellaceae (9.50%), Erwiniaceae (4.55%), and Leuconostocaceae (2.18%, \u003cb\u003eSupplementary Figure S3\u003c/b\u003e). At the genus level, the most abundant taxa included \u003cem\u003eSpiroplasma\u003c/em\u003e (67.05%), \u003cem\u003eArsenophonus\u003c/em\u003e (9.50%), and \u003cem\u003eRosenbergiella\u003c/em\u003e (4.22%, Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e). A complete summary of relative abundance percentages at the phylum, family, and genus levels is provided in \u003cb\u003eSupplementary Table S2\u003c/b\u003e.\u003c/p\u003e\u003cp\u003e \u003cb\u003e3.4 Determination of Core Gut Microbiota in\u003c/b\u003e \u003cb\u003eVespa orientalis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eOur results indicate that the core gut microbiota of \u003cem\u003eV. orientalis\u003c/em\u003e at the family level consists of Spiroplasmataceae (PS = 1.00), Morganellaceae (PS = 1.00), Halomonadaceae (PS = 1.00), Erwiniaceae (PS = 1.00), Burkholderiaceae (PS = 1.00), Moraxellaceae (PS = 0.99), Leuconostocaceae (PS = 0.99), and Microbacteriaceae (PS = 0.93) (\u003cb\u003eSupplementary Figure S4\u003c/b\u003e). At the genus level, the core microbiome includes \u003cem\u003eCarnimonas\u003c/em\u003e (PS = 0.94), \u003cem\u003eHalomonas\u003c/em\u003e (PS = 0.97), \u003cem\u003eArsenophonus\u003c/em\u003e (PS = 1.00), \u003cem\u003eFructobacillus\u003c/em\u003e (PS = 0.89), Spiroplasma (PS = 1.00), \u003cem\u003eLactococcus\u003c/em\u003e (PS = 0.93), \u003cem\u003eAcinetobacter\u003c/em\u003e (PS = 0.99), \u003cem\u003eRosenbergiella\u003c/em\u003e (PS = 1.00), \u003cem\u003eBurkholderia\u003c/em\u003e (PS = 1.00), and \u003cem\u003eLeifsonia\u003c/em\u003e (PS = 0.93) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e). To illustrate the genus-level distribution of core taxa across individual samples, a heatmap was generated (\u003cb\u003eSupplementary Figure S5\u003c/b\u003e), depicting relative abundance patterns across the four sampling sites. A complete list of prevalence and abundance scores is provided in \u003cb\u003eSupplementary Table S3\u003c/b\u003e.\u003c/p\u003e\u003ch2\u003e3.5 Landscape Impact on the Gut Microbial Community\u003c/h2\u003e\u003cp\u003eAlpha-diversity analysis measured using Faith’s Phylogenetic Diversity (Faith PD), Observed Features, and Pielou’s Evenness, indicated no significant differences in species richness across sites. However, Faith PD values resulted significantly different comparing San Ġwann and Imsida (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05). Beta-diversity analysis using Weighted UniFrac distances showed that gut microbial composition significantly differed by location (PERMANOVA: p = 0.001). Pairwise comparisons highlighted distinct clustering between Gudja \u003cem\u003evs\u003c/em\u003e Imsida (p \u0026lt; 0.01) and Gudja \u003cem\u003evs\u003c/em\u003e San Ġwann (p \u0026lt; 0.05). Additionally, PCoA analysis indicated that Gudja samples formed a separate cluster, suggesting a strong influence of local environmental conditions on gut microbiota.\u003c/p\u003e\u003cp\u003eAt the phylum level, Firmicutes were significantly more abundant in Imsida compared to Gudja (p \u0026lt; 0.05), while Proteobacteria showed a higher abundance in Gudja than in San Ġwann (p \u0026lt; 0.05) and Imsida (p \u0026lt; 0.01). At the family level, Erwiniaceae and Morganellaceae were more abundant in Gudja hornets than in San Ġwann (p \u0026lt; 0.05 for both) and Imsida (p \u0026lt; 0.05 and p \u0026lt; 0.01, respectively). On the other hand, Spiroplasmataceae levels were lower in Gudja compared to Imsida (p \u0026lt; 0.05).\u003c/p\u003e\u003cp\u003eAt the genus level, \u003cem\u003eArsenophonus\u003c/em\u003e and \u003cem\u003eRosenbergiella\u003c/em\u003e were significantly enriched in Gudja hornets compared to those in San Ġwann (both p \u0026lt; 0.05) and Imsida (p \u0026lt; 0.01 and p \u0026lt; 0.05, respectively). Conversely, \u003cem\u003eSpiroplasma\u003c/em\u003e levels were lower in Gudja compared to Imsida (p \u0026lt; 0.05).\u003c/p\u003e\u003cp\u003eDifferential Abundance Analysis (DAA) revealed site-specific differences in microbial taxa. In Gudja vs. Imsida, \u003cem\u003eArsenophonus\u003c/em\u003e was significantly more abundant in Gudja, whereas \u003cem\u003eSpiroplasma\u003c/em\u003e, \u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, and \u003cem\u003eEnterobacter\u003c/em\u003e were more common in Imsida samples (Log fold change = ± 3, \u003cb\u003eSupplementary Figure S6\u003c/b\u003e). Comparisons between Gudja and San Ġwann showed that \u003cem\u003eArsenophonus\u003c/em\u003e, \u003cem\u003eRosenbergiella\u003c/em\u003e, \u003cem\u003eDysgonomonas\u003c/em\u003e, \u003cem\u003eGluconobacter\u003c/em\u003e, and \u003cem\u003eAcinetobacter\u003c/em\u003e were enriched in Gudja, while \u003cem\u003eHafnia-Obesumbacterium\u003c/em\u003e was significantly higher in San Ġwann (Log fold change = ± 3, \u003cb\u003eSupplementary Figure S7\u003c/b\u003e). Similarly, in San Ġwann vs. Imsida, \u003cem\u003eThiomicrorhabdus\u003c/em\u003e, \u003cem\u003eBlautia\u003c/em\u003e, \u003cem\u003eStaphylococcus\u003c/em\u003e, \u003cem\u003eCommensalibacter\u003c/em\u003e, and \u003cem\u003eProteus\u003c/em\u003e were enriched in San Ġwann, while \u003cem\u003eAcinetobacter\u003c/em\u003e was depleted (Log fold change = ± 3, \u003cb\u003eSupplementary Figure S8\u003c/b\u003e). Finally, hornets sampled in the Qawra site showed an enrichment of more than 15 microbial genera, including \u003cem\u003eCarnimonas, Arsenophonus, Frischella, Snodgrassella, Gilliamella\u003c/em\u003e, and \u003cem\u003eEnterobacter\u003c/em\u003e, compared to hornets from San Ġwann and Gudja (Log fold change = ± 3.5, \u003cb\u003eSupplementary Figure S9 and S10\u003c/b\u003e).\u003c/p\u003e\u003ch2\u003e3.6 Effect of Diet on the Gut Microbial Community\u003c/h2\u003e\u003cp\u003eWeighted UniFrac (beta-diversity) analysis revealed a strong difference in gut microbiome composition between honey bee-feeding and cat food-scavenging hornets (PERMANOVA, p \u0026lt; 0.01). At the phylum level, Firmicutes were significantly more abundant in hornets consuming cat food (p \u0026lt; 0.05), while Proteobacteria were more prevalent in those feeding on honey bees (p \u0026lt; 0.05). At the family level, Morganellaceae was enriched in honey bee-feeding hornets (p \u0026lt; 0.01), whereas cat food-fed hornets exhibited a higher relative abundance of Spiroplasmataceae (p \u0026lt; 0.05). At the genus level, this trend was reflected in the higher relative abundance of \u003cem\u003eArsenophonus\u003c/em\u003e in honey bee-feeding hornets (p \u0026lt; 0.01) and \u003cem\u003eSpiroplasma\u003c/em\u003e in cat food-feeding hornets (p \u0026lt; 0.05).\u003c/p\u003e\u003cp\u003eDifferential abundance analysis (DAA) further highlighted key microbial differences based on diet. \u003cem\u003eEnterobacter\u003c/em\u003e was significantly more abundant in hornets consuming cat food, while \u003cem\u003eArsenophonus\u003c/em\u003e was enriched in honey bee-feeding hornets (Log fold change = ± 3, \u003cb\u003eSupplementary Figure S11\u003c/b\u003e). Additionally, significant microbiome differences were detected between hornets scavenging cat food in Qawra and those in Imsida. Specifically, \u003cem\u003eArsenophonus\u003c/em\u003e, \u003cem\u003eGilliamella\u003c/em\u003e, \u003cem\u003eWeissella\u003c/em\u003e, and \u003cem\u003eFructobacillus\u003c/em\u003e were more abundant in Qawra, whereas \u003cem\u003ePlanococcus\u003c/em\u003e, \u003cem\u003eSalinimicrobium\u003c/em\u003e, and \u003cem\u003eSnodgrassella\u003c/em\u003e were more prevalent in Imsida (Log fold change = ± 3).\u003c/p\u003e\u003ch2\u003e3.7 Gut microbiome Total Bacteria and Pathogens Load\u003c/h2\u003e\u003cp\u003eqPCR results showed that the total bacteria absolute abundance varies between Log 6 and 9 among the single sampled hornets (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eA). However, no significant differences were highlighted when the different sampling site were compared. Considering the pathogens load, \u003cem\u003eN. ceranae\u003c/em\u003e was detected in the 97.15% of the sampled hornets (70 individuals), while \u003cem\u003eSerratia\u003c/em\u003e (\u003cem\u003eluxS\u003c/em\u003e gene) and \u003cem\u003eC. bombi\u003c/em\u003e frequency of positive detection was 71.43% and 62.86%, respectively. \u003cem\u003eC. bombi\u003c/em\u003e exhibited the widest absolute abundance per hornet (Log 4.29 ± 3.58, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eD) respect the other pathogens detected, followed by \u003cem\u003eN. ceranae\u003c/em\u003e (Log 2.64 ± 0.75, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eB) and \u003cem\u003eSerratia\u003c/em\u003e (Log 1.17 ± 0.87, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). When the sampling site were considered, no significant variations were highlighted in the hornets’ gut microbiome pathogens load for \u003cem\u003eN. ceranae\u003c/em\u003e and \u003cem\u003eC. bombi\u003c/em\u003e. Conversely, \u003cem\u003eSerratia\u003c/em\u003e absolute abundance of the hornets sampled in Imsida (1.76 ± 0.81 \u003cem\u003eluxS\u003c/em\u003e gene copies/gut) was higher than the individuals sampled in Gudja (0.99 ± 0.68 \u003cem\u003eluxS\u003c/em\u003e gene copies/gut) and San Ġwann (0.71 ± 0.81 \u003cem\u003eluxS\u003c/em\u003e gene copies/gut) Malta Island sites (\u003cem\u003ep\u003c/em\u003e \u0026lt; 0.05, Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eC). No positive hornets for the pathogens \u003cem\u003eN. apis, N. bombi, C. mellificae, L. passim, A. bombi, Listeria\u003c/em\u003e, and \u003cem\u003eSalmonella\u003c/em\u003e. were found. All the qPCR results are reported in \u003cb\u003eSupplementary Table S4\u003c/b\u003e.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003e \u003cb\u003eComposition of the Gut Microbiota in\u003c/b\u003e \u003cb\u003eVespa orientalis\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe gut microbiota of \u003cem\u003eV. orientalis\u003c/em\u003e was dominated by Firmicutes and Proteobacteria, consistent with findings in previous studies on other \u003cem\u003eVespa\u003c/em\u003e species [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e–\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. Additionally, Bacteroidetes and Actinobacteria were present, aligning with most prior studies, except for [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e], who did not report these phyla. These results suggest a degree of conservation in the hornet gut microbiome at the phylum level, likely reflecting shared physiological traits and dietary habits across \u003cem\u003eVespa\u003c/em\u003e species. However, at lower taxonomic levels, significant variation was observed, reinforcing previous reports that gut composition diverges among \u003cem\u003eVespa\u003c/em\u003e species [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The most abundant genera in \u003cem\u003eV. orientalis\u003c/em\u003e were \u003cem\u003eSpiroplasma\u003c/em\u003e and \u003cem\u003eArsenophonus\u003c/em\u003e, with \u003cem\u003eSpiroplasma\u003c/em\u003e having been reported in \u003cem\u003eVespa\u003c/em\u003e only in the recent study by [\u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e20\u003c/span\u003e]. Interestingly, \u003cem\u003eArsenophonus\u003c/em\u003e has not been previously documented in hornet gut microbiota. This suggests that some members of the microbiome may be species-specific or influenced by environmental conditions. The predominance of \u003cem\u003eArsenophonus\u003c/em\u003e in hornets from Gudja, which was also the most sampled location, raises the possibility of geographical or ecological factors shaping microbiota composition.\u003c/p\u003e\u003cp\u003eSeveral other genera identified in this study, including \u003cem\u003eFructobacillus\u003c/em\u003e, \u003cem\u003eLeuconostoc\u003c/em\u003e, \u003cem\u003eLactococcus\u003c/em\u003e, \u003cem\u003eWeissella\u003c/em\u003e, \u003cem\u003eGilliamella\u003c/em\u003e, \u003cem\u003eCarnimonas\u003c/em\u003e, \u003cem\u003eSnodgrassella\u003c/em\u003e, and \u003cem\u003ePantoea\u003c/em\u003e, were also present in previous \u003cem\u003eVespa\u003c/em\u003e gut microbiome studies [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e]. The detection of \u003cem\u003eGilliamella\u003c/em\u003e and \u003cem\u003eSnodgrassella\u003c/em\u003e, which are core members of the honey bee microbiota, suggests a potential microbial exchange between hornets and their honey bee prey. Otherwise, our results designated that the main \u003cem\u003eV. orientalis\u003c/em\u003e microbiome core family are Spiroplasmataceae, Morganellaceae, Halomonadaceae, Erwiniaceae, Burkholderiaceae, Moraxellaceae, Leuconostocaceae, and Microbacteriaceae. Specifically, \u003cem\u003eV. orientalis\u003c/em\u003e core gut microbiome genus belonging to \u003cem\u003eCarnimonas\u003c/em\u003e, \u003cem\u003eHalomonas\u003c/em\u003e, \u003cem\u003eArsenophonus\u003c/em\u003e, \u003cem\u003eFructobacillus\u003c/em\u003e, \u003cem\u003eSpiroplasma\u003c/em\u003e, \u003cem\u003eLactococcus\u003c/em\u003e, \u003cem\u003eAcinetobacter\u003c/em\u003e, \u003cem\u003eRosenbergiella\u003c/em\u003e, \u003cem\u003eBurkholderia\u003c/em\u003e, and \u003cem\u003eLeifsonia\u003c/em\u003e.\u003c/p\u003e\u003cp\u003e \u003cb\u003e4.2 Beekeeper Survey and\u003c/b\u003e \u003cb\u003eVespa orientalis\u003c/b\u003e \u003cb\u003eImpact on Apiaries\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe beekeeper survey conducted between 2022 and 2024 provides valuable insights into the perceived impact of \u003cem\u003eV. orientalis\u003c/em\u003e on honey bee colonies in Malta. Across all three years, 100% of responding beekeepers reported \u003cem\u003eV. orientalis\u003c/em\u003e sightings, confirming its continued presence in Maltese apiaries. However, reported colony losses due to hornet predation fluctuated, with a peak in 2022 (63.8%), a decline in 2023 (29.4%), and a resurgence in 2024 (59.5%). This pattern suggests that 2023 was an anomalous year with reduced hornet activity, potentially influenced by external ecological factors.\u003c/p\u003e\u003cp\u003eThe decline in colony losses reported in 2023 could be attributed to several possible factors. One explanation is climatic variability, as beekeepers cited prolonged cold weather and food scarcity as potential stressors on hornet populations (\u003cb\u003eAppendix 1\u003c/b\u003e). A colder-than-usual season could have delayed hornet colony establishment, reducing predation pressure on honey bee colonies [\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]. Human intervention, including trapping and manual removal efforts, was also reported as a potential factor, though declining beekeeper engagement in control measures over time suggests that this alone may not fully explain the observed trend. Furthermore, an increase in alternative protein sources in urban and peri-urban areas could have lessened the reliance of \u003cem\u003eV. orientalis\u003c/em\u003e on honey bee predation, resulting in a temporary decline in impact. These possibilities highlight the need for further ecological monitoring to determine how climatic and environmental variables influence hornet population dynamics over time.\u003c/p\u003e\u003cp\u003eIntervention efforts by beekeepers showed a general decline over the three-year period. In 2022, 82.8% of beekeepers reported taking action against \u003cem\u003eV. orientalis\u003c/em\u003e, but this fell to 73.5% in 2023 and 75.7% in 2024. While slightly increasing again in 2024, this decline may indicate reduced beekeeper engagement, changes in hornet activity, or shifting perceptions of intervention effectiveness. The effectiveness of control strategies was also increasingly questioned, with only 43.2% of beekeepers in 2024 finding their interventions successful, down from 52.9% in 2023. The increasing failure of control efforts highlights the need to reassess integrated management strategies.\u003c/p\u003e\u003cp\u003eThe seasonal trend in honey bee losses supports the idea that \u003cem\u003eV. orientalis\u003c/em\u003e exerts the highest predation pressure between July and October. This period corresponds with peak hornet foraging activity, likely driven by increased protein demands for colony development. The microbiome data from honey bee-fed hornets, particularly the enrichment of \u003cem\u003eArsenophonus\u003c/em\u003e, aligns with this trend, suggesting that microbial signatures in hornet gut communities could serve as indirect indicators of predation intensity. Future studies could explore whether microbiome analysis can complement traditional survey data in monitoring hornet foraging behaviours and their seasonal impacts on beekeeping.\u003c/p\u003e\u003cp\u003eThe seasonal trend in honey bee losses suggests that \u003cem\u003eV. orientalis\u003c/em\u003e exerts its highest predation pressure between July and October, coinciding with peak foraging activity. This period likely reflects increased protein demands for colony development, as hornet larvae require protein-rich diets, which worker hornets obtain by hunting insects, including honey bees, or scavenging protein sources in urban waste. In contrast, adult hornets primarily consume carbohydrates, such as nectar, honeydew, and fruit, adapting their diet based on seasonal availability.\u003c/p\u003e\u003cp\u003eMicrobiome analysis of honey bee-fed hornets revealed enrichment of \u003cem\u003eArsenophonus\u003c/em\u003e, a bacterial genus associated with honey bee gut communities, further supporting the dietary shift from carbohydrate-rich to protein-based foraging. These microbial signatures in the hornet gut may serve as indirect indicators of predation intensity.\u003c/p\u003e\u003cp\u003eAs this study provides only a single time-point snapshot of the V. orientalis gut microbiota, longer-term research is needed to capture seasonal shifts. Earlier in the active season, when hornets rely more on carbohydrate sources, their microbiota may differ significantly from the profiles observed during peak predation. Future longitudinal studies could explore these dietary-driven microbiome changes, enhancing our understanding of hornet ecology, pathogen transmission risks, and the potential for microbiome analysis as a complementary tool for monitoring seasonal foraging behaviours and their impacts on beekeeping.\u003c/p\u003e\u003ch2\u003e4.3 Diet as Driver of Microbial Variation\u003c/h2\u003e\u003cp\u003ePhylogenetic diversity (Faith PD) showed no significant difference between honey bee and cat food-feeding hornets. This suggests that despite potential dietary-driven compositional shifts, both groups maintained similar levels of microbial phylogenetic diversity. These findings align with [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e], who reported comparable alpha diversity values between \u003cem\u003eVespa mandarinia\u003c/em\u003e and \u003cem\u003eVespa simillima\u003c/em\u003e, despite differences in diet. Suenami et al. [\u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e] proposed that core OTUs in hornets are primarily diet-dependent rather than coevolved with the host, which may explain the similarity in gut diversity despite dietary differences. Similarly, the results of the alpha diversity metrics indicate that gut microbiota richness and evenness were comparable between hornets feeding on cat food and honey bees. No significant differences were detected in species richness (Observed Features) or evenness (Evenness), suggesting that food source did not influence overall microbial diversity. However, while not statistically significant, cat food-feeding hornets exhibited a trend toward lower evenness, indicating a potential dominance of specific bacterial taxa. This pattern was further supported by Differential Abundance Analysis (DAA), which identified several genera contributing to microbiota differences across food sources. Hornets feeding on cat food exhibited a significantly higher abundance of \u003cem\u003eEnterobacter\u003c/em\u003e, while those feeding on honey bees had increased levels of \u003cem\u003eArsenophonus\u003c/em\u003e. This pattern aligns with findings from Section \u003cspan refid=\"Sec19\" class=\"InternalRef\"\u003e4.4\u003c/span\u003e, where hornets from Gudja, a natural apiary site, were enriched in \u003cem\u003eArsenophonus\u003c/em\u003e, while those from Imsida, an urban site, showed higher levels of \u003cem\u003eEnterobacter\u003c/em\u003e. \u003cem\u003eEnterobacter\u003c/em\u003e, a member of Enterobacteriaceae, is known to occur in raw meat and has been identified in spoiled pet food [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Its presence in cat food-feeding hornets suggests dietary transmission from scavenged protein-rich food sources. \u003cem\u003eEnterobacter\u003c/em\u003e has been previously detected in other insects, including tsetse flies and fruit flies [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] and was also reported in \u003cem\u003eVespula germanica\u003c/em\u003e wasp stings [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. The potential pathogenicity of \u003cem\u003eEnterobacter\u003c/em\u003e in hornets warrants further investigation.\u003c/p\u003e\u003cp\u003eInterestingly, some honey bee-associated bacteria, such as \u003cem\u003eGilliamella\u003c/em\u003e, \u003cem\u003eSnodgrassella\u003c/em\u003e, and \u003cem\u003eBifidobacterium\u003c/em\u003e, did not show significant abundance differences between the two food sources. Previous studies on \u003cem\u003eVespa\u003c/em\u003e species linked the presence of \u003cem\u003eGilliamella\u003c/em\u003e to honey bee predation [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e]. The lack of a significant difference in this study could suggest that these microbes may not be strictly diet-dependent in \u003cem\u003eV. orientalis\u003c/em\u003e. Alternatively, this pattern could be explained by Malta’s relatively small geographic scale and the short distances between sites, allowing hornets from urban areas to visit apiaries before being sampled. Although research on the flight range of \u003cem\u003eV. orientalis\u003c/em\u003e is limited, studies on \u003cem\u003eVespa velutina\u003c/em\u003e (Asian hornet) suggest that workers can forage up to around 1km from their nests [\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e]. Given the behavioural and ecological similarities among hornet species, it is plausible that \u003cem\u003eV. orientalis\u003c/em\u003e exhibits comparable foraging distances, allowing individuals to easily move between urban and beekeeping environments. This mobility could explain the presence of honey bee-associated microbes in hornets sampled from urban sites, supporting the possibility of microbial exchange across different foraging habitats.\u003c/p\u003e\u003ch2\u003e4.4 Geographic Variation and Environmental Influence on Microbiota\u003c/h2\u003e\u003cp\u003eIn addition to diet, site-based differences were notable, particularly in Gudja vs. Imsida comparisons. Hornets from Gudja showed enrichment in \u003cem\u003eArsenophonus\u003c/em\u003e, while those from Imsida had higher levels of \u003cem\u003eHafnia-Obesumbacterium, Serratia\u003c/em\u003e, and \u003cem\u003eEnterobacter\u003c/em\u003e—all of which are associated with raw meat spoilage [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e, \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e]. This further supports the idea that diet is a key driver of microbiota composition.\u003c/p\u003e\u003cp\u003e \u003cem\u003eArsenophonus\u003c/em\u003e, on the other hand, is a well-documented insect-associated symbiont, with roles ranging from male-killing in some hosts to nutritional mutualism [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e, \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e]. It has been identified in honey bees, where it was initially mistaken for the pathogen \u003cem\u003eArsenophonus nasoniae\u003c/em\u003e but later confirmed as a unique strain (\u003cem\u003eA. apicola\u003c/em\u003e) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e].\u003c/p\u003e\u003cp\u003e \u003cem\u003eArsenophonus\u003c/em\u003e has previously been identified in honey bee colonies, where it was associated with poor colony health [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]. The detection of \u003cem\u003eArsenophonus\u003c/em\u003e in hornets feeding on honey bees indicates that predation may facilitate microbial transfer between predator and prey, potentially influencing pathogen dynamics within apiaries. These findings highlight that diet significantly shapes \u003cem\u003eV. orientalis\u003c/em\u003e' microbiome, possibly through differences in nutrient composition, exposure to gut microbiota from prey, and environmental microbial sources.\u003c/p\u003e\u003cp\u003eBeta diversity analysis revealed clustering patterns in microbial composition based on food source and location. Bray-Curtis dissimilarity indicated some degree of separation between groups. The Unweighted UniFrac analysis showed no significant differences in microbial presence/absence, suggesting that rare taxa did not drive the observed variation. However, Weighted UniFrac analysis revealed significant differences between honey bee-feeding and cat food-feeding hornets, highlighting that taxonomic abundance was a key factor in gut microbiota differences. Our results suggest that location might play a role in microbial composition, as indicated by the significant differences in Weighted UniFrac distances between Gudja and Imsida, as well as Gudja and San Ġwann. Gudja samples exhibited a distinct microbial community compared to other sites, even when compared to San Ġwann, which was also a honey bee-feeding site. These findings are consistent with previous studies suggesting that geographical location (and not just diet) can shape gut microbiota composition. The observed microbial differences between Gudja and the other study sites may reflect differences in environmental resource availability, such as floral resources, host genetics, prey abundance and prey microbiota, or human-associated food sources. This highlights the importance of landscape composition in shaping hornet gut microbiota, warranting further study into how urban or peri-urban \u003cem\u003evs.\u003c/em\u003e rural environments influence microbial acquisition patterns.\u003c/p\u003e\u003cp\u003e \u003cb\u003e4.5 Spillover\u003c/b\u003e \u003cb\u003evs.\u003c/b\u003e \u003cb\u003eSpillback: Rethinking\u003c/b\u003e \u003cb\u003eV. orientalis\u003c/b\u003e\u003cb\u003e' Role in Pathogen Dynamics\u003c/b\u003e\u003c/p\u003e\u003cp\u003eThe role of \u003cem\u003eVespa orientalis\u003c/em\u003e as a pathogen reservoir rather than a primary spillover vector mirrors patterns observed in invasive species. A similar dynamic has been documented in \u003cem\u003eCallosciurus erythraeus\u003c/em\u003e, an invasive squirrel in Japan, which has been shown to amplify local parasite burdens by acting as an additional host for both native and exotic ectoparasites [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]. This process, known as spillback, occurs when an invasive species does not introduce new pathogens but instead facilitates their persistence and circulation within an ecosystem [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e]. By serving as additional hosts, invasive organisms can disrupt the balance between native species and pathogens, increasing infection risks.\u003c/p\u003e\u003cp\u003eWhile hornets have previously been considered vectors capable of transmitting pathogens to honey bees (spillover) [\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e, \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e, \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e] our findings suggest a possible alternative spillback scenario, whereby a pathogen is transmitted from a new host species (\u003cem\u003eV. orientalis\u003c/em\u003e) back to its original host or ecosystem, potentially altering infection patterns or pathogen prevalence. Despite its ecological significance, spillback remains underexplored, partly due to the difficulty of establishing pathogen transmission directionality. The stochastic presence of pathogens and viruses reported by [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e] supports the hypothesis that hornets do not naturally harbour these pathogens but rather acquire them from the environment or prey, indicating that hornets likely act as pathogen reservoirs and contribute to a spillback dynamic. Environmental factors such as increasing urbanisation, climate change, and resource availability may further shape microbial spillback dynamics, altering pathogen transmission risks between hornets, honey bees, other insects and humans. Understanding how these landscape-level changes influence the gut microbiome of \u003cem\u003eV. orientalis\u003c/em\u003e can provide deeper insights into the broader socioecological consequences of invasive species, particularly within a One Health framework.\u003c/p\u003e\u003cp\u003eOur findings confirm that \u003cem\u003eV. orientalis\u003c/em\u003e harbours \u003cem\u003eNosema ceranae\u003c/em\u003e and \u003cem\u003eCrithidia bombi\u003c/em\u003e, both of which were detected in a large proportion of sampled hornets and have been previously reported in this species [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e, \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e]. These results suggest a potential spillback mechanism, though further research is needed to confirm whether \u003cem\u003eV. orientalis\u003c/em\u003e plays an active role in pathogen transmission. The detection of bee-specific pathogens in honey bee-feeding hornets suggests that hornets may acquire these pathogens directly from their prey, reinforcing their role as pathogen sinks rather than primary reservoirs. However, the persistence of these microbes within the hornet gut and the potential for secondary transmission remain uncertain. Research on other predator insects has shown that some microbial species can survive passage through the gut and may be excreted in a viable form (e.g., in faeces or regurgitation), which could provide an indirect transmission pathway back to honey bees or the environment [\u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e]. Further studies are needed to assess the viability of \u003cem\u003eNosema ceranae\u003c/em\u003e and \u003cem\u003eCrithidia bombi\u003c/em\u003e post-digestion and determine whether hornets contribute to pathogen cycling in apiary environments. This is particularly relevant for pollinator health and ecosystem stability, two key pillars of the One Health approach.\u003c/p\u003e\u003cp\u003eThe dietary-driven microbial shifts in \u003cem\u003eV. orientalis\u003c/em\u003e, such as the enrichment of \u003cem\u003eArsenophonus\u003c/em\u003e in honey bee-fed individuals and \u003cem\u003eEnterobacter\u003c/em\u003e in cat food-scavenging hornets, closely parallel observations in \u003cem\u003eC. erythraeus\u003c/em\u003e, where diet influenced the prevalence of different bacterial taxa. Additionally, both studies highlight significant spatial variation in microbial loads, suggesting that local environmental conditions may shape pathogen spillback risks. While this suggests a strong predator-prey microbial exchange, the one-way nature of this transfer remains to be fully established. Some microbial taxa, such as \u003cem\u003eArsenophonus\u003c/em\u003e, have been identified as endosymbionts in honey bees [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e], yet their functional role in hornets is still unclear. If \u003cem\u003eArsenophonus\u003c/em\u003e can persist and proliferate within \u003cem\u003eV. orientalis\u003c/em\u003e, it may challenge the notion that hornets strictly function as microbial sinks rather than as potential secondary hosts or facilitators of microbial exchange.\u003c/p\u003e\u003cp\u003eThe detection of \u003cem\u003eCrithidia bombi\u003c/em\u003e in \u003cem\u003eV. orientalis\u003c/em\u003e may also suggest a broader dietary range than previously documented. While hornets are known to primarily prey on honey bees, the presence of \u003cem\u003eC. bombi\u003c/em\u003e, a pathogen typically associated with bumble bees, raises the possibility that \u003cem\u003eV. orientalis\u003c/em\u003e may also prey on or scavenge from \u003cem\u003eBombus\u003c/em\u003e species or other solitary bees as is known with other \u003cem\u003eVespa\u003c/em\u003e species such as \u003cem\u003eVespa velutina nigrithorax\u003c/em\u003e [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e]. This could have significant ecological implications, as bumble bees are essential pollinators, and increased predation pressure from \u003cem\u003eV. orientalis\u003c/em\u003e could exacerbate population declines in wild pollinators. Alternatively, hornets might acquire \u003cem\u003eC. bombi\u003c/em\u003e indirectly through floral contamination, as \u003cem\u003eC. bombi\u003c/em\u003e can persist on flowers and be transmitted via shared foraging sites [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. Further research is needed to determine whether \u003cem\u003eV. orientalis\u003c/em\u003e actively preys on bumble bees or acquires \u003cem\u003eC. bombi\u003c/em\u003e through environmental exposure, and what implications this may have for pollinator pathogen dynamics.\u003c/p\u003e\u003cp\u003eThe gut microbiota of \u003cem\u003eV. orientalis\u003c/em\u003e revealed clear dietary influences, with enrichment of \u003cem\u003eArsenophonus\u003c/em\u003e in honey bee-feeding hornets and \u003cem\u003eEnterobacter\u003c/em\u003e in those scavenging on cat food. These findings strongly indicate a microbial exchange between predator and prey rather than \u003cem\u003eV. orientalis\u003c/em\u003e acting as a primary pathogen reservoir for honey bees. The predatory behaviour of hornets involves immediate and lethal interactions, making microbial acquisition from honey bees a likely one-way transfer. However, potential secondary transmission routes, such as environmental shedding, faecal deposition, or regurgitation, remain unexamined and warrant further study.\u003c/p\u003e\u003ch2\u003e4.6 Pathogen Detection and One Health Implications\u003c/h2\u003e\u003cp\u003eOur qPCR-based pathogen screening primarily targeted bee-associated microbes. Of the eight tested pathogens, only \u003cem\u003eNosema ceranae\u003c/em\u003e, \u003cem\u003eSerratia\u003c/em\u003e, and \u003cem\u003eCrithidia bombi\u003c/em\u003e were detected, with \u003cem\u003eSerratia\u003c/em\u003e exhibiting low abundance. The presence of \u003cem\u003eSerratia\u003c/em\u003e in \u003cem\u003eV. orientalis\u003c/em\u003e suggests potential exposure to human-associated environments, such as urban waste or agricultural runoff. \u003cem\u003eSerratia\u003c/em\u003e species are opportunistic pathogens with relevance to both insect and human health. Given that hornets frequently scavenge in human-dominated habitats, their potential role in maintaining environmental reservoirs of foodborne or antimicrobial-resistant bacteria cannot be overlooked. We also screened for two human pathogens, \u003cem\u003eListeria\u003c/em\u003e and \u003cem\u003eSalmonella\u003c/em\u003e, both of which tested negative in all samples, consistent with findings by Zucca et al., [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. This suggests that \u003cem\u003eV. orientalis\u003c/em\u003e may not serve as a primary carrier of these pathogens. However, broader screening across different geographic regions and dietary contexts is necessary to fully evaluate potential public health risks.\u003c/p\u003e\u003cp\u003eIntegrating a One Health perspective, future research should evaluate whether \u003cem\u003eV. orientalis\u003c/em\u003e contributes to pathogen spillover or spillback dynamics within apiaries, urban environments, and broader ecosystems. The intersection of ecological, veterinary, and public health considerations will be essential in formulating evidence-based management strategies that mitigate risks associated with \u003cem\u003eV. orientalis\u003c/em\u003e in both native and invaded habitats.\u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThis study provides the first comprehensive characterisation of the gut microbiota of \u003cem\u003eVespa orientalis\u003c/em\u003e, revealing its dynamic composition influenced by both environmental factors and diet. While the gut microbiota at the phylum level aligns with previous research on other \u003cem\u003eVespa\u003c/em\u003e species, significant differences at the family and genus levels highlight the species-specific and habitat-driven nature of microbial communities.\u003c/p\u003e\u003cp\u003eOur findings demonstrate that \u003cem\u003eV. orientalis\u003c/em\u003e exhibits distinct microbiota compositions across different landscapes, suggesting that microbial plasticity may contribute to its resilience in both urban and natural environments. The pronounced enrichment of \u003cem\u003eEnterobacter\u003c/em\u003e in hornets scavenging on cat food and \u003cem\u003eArsenophonus\u003c/em\u003e in honey bee-feeding individuals underscores the role of diet in shaping microbial diversity. This suggests that urban scavenging behaviours could alter gut microbial balance, while honey bee predation may facilitate microbial exchange between predator and prey. The presence of bee-associated microbes in \u003cem\u003eV. orientalis\u003c/em\u003e further supports a spillback dynamic rather than a direct spillover effect, indicating that the hornet primarily functions as a microbial reservoir rather than an active pathogen vector.\u003c/p\u003e\u003cp\u003eThese insights into \u003cem\u003eV. orientalis\u003c/em\u003e microbiota and its potential interactions with honey bee pathogens contribute to a broader understanding of the ecological and epidemiological implications of this species. Future research should explore seasonal shifts in gut microbiota, the viability of pathogen transmission, and the potential consequences of microbial exchange within apiary environments. Integrating these findings into One Health frameworks could support the development of targeted management strategies and even open new avenues for biological control, such as microbial-based interventions to regulate \u003cem\u003eV. orientalis\u003c/em\u003e populations, ultimately mitigating its impact on pollinators, ecosystems, and public health.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eCompeting Interests \u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eThe authors declare no conflict of interests. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eEthical review and approval were waived, because the Italian law does not require and ethical approval for tests performed on arthropods with exceptions of cephalopods according to the Italian D.L. 4 March 2014 n. 26, and Italian implementing decree following the European regulation 2010/63/UE. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors Contribution please add any other contribution type or any contributor. \u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eD.M and S.C. were involved in the experimental design; S.C., M.M., and C.B. in formal NGS and qPCR analysis; L.B. performed bioinformatic analysis; D.A, S.C and C.B were involved in statistical analysis and data curation; J.S. carried out the \u003cem\u003eV. orientalis\u003c/em\u003e impact survey; D.A. and D.D.G. coordinated the research work; S.C and C.B wrote the manuscript; D.A., D.M., L.B., and D.D.G., revised the manuscript. D.A., S.C., D.M., and D.D.G., were involved in funding acquisition. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData availability statement\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eNGS raw sequence data have been submitted to NCBI repository under the Sequence Read Archive (SRA) databases under the Bioproject N\u0026deg; PRJNA1232968, biosamples SAMN47255446 - SAMN47255585.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eThis study received the financial support from the Tertiary Education Scholarships Scheme by the Ministry for Education, Sport, Youth, Research and Innovation in Malta (TESS 2022). \u003c/p\u003e\n\u003cp\u003eThis study was also carried out within the Agritech National Research Center and received funding from the European Union Next-GenerationEU - PIANO NAZIONALE DI RIPRESA E RESILIENZA (PNRR) \u0026ndash; MISSIONE 4 COMPONENTE 2, INVESTIMENTO 1.4 \u0026ndash; D.D. 1032 17/06/2022, CN00000022. \u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e \u003c/p\u003e\n\u003cp\u003eWe wish to thank beekeepers of the Malta Beekeepers\u0026apos; Association VO 1527, who have participated to the survey on \u003cem\u003eV. orientalis\u003c/em\u003e incidence in Malta.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eArcher M. 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Ecology and Evolution. 2023;13(7):e10379.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Spiroplasmataceae, Enterobacter, Arsenophonus, Crithidia, Nosema, spillback","lastPublishedDoi":"10.21203/rs.3.rs-6179679/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-6179679/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eVespa orientalis\u003c/em\u003e (Oriental hornet) is expanding its range worldwide, raising concerns about its predatory impact on honey bees and potential health risks to humans. This study provides the first comprehensive description of the \u003cem\u003eV. orientalis\u003c/em\u003e gut microbiome, explores how diet and location influence microbial composition, and bee pathogens reservoir. Adult hornets with different feeding behaviors were sampled from four urban and natural sites in Malta. 16S rRNA gene sequencing revealed a gut microbiota dominated by Firmicutes and Proteobacteria, with key genera including \u003cem\u003eCarnimonas\u003c/em\u003e, \u003cem\u003eArsenophonus\u003c/em\u003e, and \u003cem\u003eRosenbergiella.\u003c/em\u003e Significant compositional shifts were observed in relation to diet and sampling location, suggesting that environment and diet significantly shape the hornet gut community. Moreover, detection of certain honey bee-associated microbes, such as \u003cem\u003eGilliamella\u003c/em\u003e and \u003cem\u003eSnodgrassella\u003c/em\u003e, points to potential microbial exchange between predator and prey. Quantitative PCR targeting bee and human pathogens detected high prevalence rates of \u003cem\u003eNosema ceranae\u003c/em\u003e, \u003cem\u003eCrithidia bombi\u003c/em\u003e, and \u003cem\u003eSerratia\u003c/em\u003e, while \u003cem\u003eListeria\u003c/em\u003e, \u003cem\u003eSalmonella\u003c/em\u003e, and other bee pathogens were absent. Our findings suggest \u003cem\u003eV. orientalis\u003c/em\u003e may function more as a pathogen reservoir rather than a primary spillover vector and lays the groundwork for targeted management strategies to mitigate its impact on apiculture and broader ecosystem services.\u003c/p\u003e","manuscriptTitle":"Rethinking spillover risks: first description of the Vespa orientalis gut microbiome and its impact on honeybee and human health","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-04-22 16:12:53","doi":"10.21203/rs.3.rs-6179679/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"cd40286a-f782-4038-a66e-7d91df41fddd","owner":[],"postedDate":"April 22nd, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-28T07:53:41+00:00","versionOfRecord":[],"versionCreatedAt":"2025-04-22 16:12:53","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-6179679","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-6179679","identity":"rs-6179679","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}