{"paper_id":"3379e1a2-2d5f-4a36-8b6b-e26218fb1b1c","body_text":"Negative effects of increased ozone concentrations and heat stress on bumblebees are exacerbated by microplastics | 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 Negative effects of increased ozone concentrations and heat stress on bumblebees are exacerbated by microplastics Gwen Kühn, Marco M. Rupprecht, Magdalena M. Mair, Jan B. Stöckl, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9320368/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 The intensity of environmental stressors increases due to global change. Under natural conditions, insect pollinators are experiencing multiple stressors simultaneously which may exacerbate the negative effects of individual stressors. Using a fully crossed factorial design, we investigated the effects of ozone, heat, and LDPE microplastics (MP) on Bombus terrestris health. Changes in the fat body proteome suggest that ozone induces an oxidative stress response, heat induces changes in the metabolism, and MP induces tissue damage responses and detoxification reactions. Among the single stressors, only MP increased bumblebee mortality. However, in combination with MP, also ozone, heat, and both combined increased the mortality. Here the effect strength exceeded expectations, suggesting synergistic effects. We presume a reduced heat resistance in MP-exposed bumblebees as one possible underlying mechanism. Our study suggests that the progressive environmental accumulation of MP, rising temperatures and the associated increase in ozone levels could pose a serious health risk to pollinators in the future. Terrestrial Ecology Entomology Multiple stressors LDPE fat body proteome synergistic effects Figures Figure 1 Figure 2 Figure 3 Figure 4 Teaser Ozone and heat only increase bumblebee mortality combined with microplastics, but then the magnitude exceeds expectations. Introduction Insect pollinators support the majority of the world’s plant diversity and the organisms that are associated with it ( 1 ). About 20 percent of the plants that benefit from insect pollination depend on bee pollination ( 1 ). Among wild bees, bumblebees are of particular ecological importance, as many bumblebees are generalist pollinators essential for a large number of plant species (e.g. 2 ). However, in Europe for instance, 21 percent of the 63 bumblebee species assessed by the International Union for Conservation of Nature (IUCN) are classified as threatened ( 3 ). Currently, stressors resulting from anthropogenic environmental changes pose severe threats to global biodiversity and associated ecosystem functioning (e.g. 4 ). The most important stressors endangering bumblebee health include habitat loss, fragmentation, degradation and associated challenges, as well as climate change, pathogens, pesticides, and further anthropogenic pollutants (e.g. 3 ). In their natural environment, bumblebees are not exposed to isolated single stressors but instead are confronted with combinations of several stressors at the same time ( 5 ). On top of that, multiple stressors can interact in complex ways, causing effects that deviate from expected combined effects ( 3 ). Generally, multiple stressors can lead to three types of effects in organisms: First, effects can be as expected, where the combined effect reflects the joint influence of individual stressor effects (see Schäfer & Piggott for different methods for effect combination, 6 ). Expected combined effects have been observed in honey bees ( Apis mellifera ), where the exposure to three different metals, arsenic, lead, and copper slowed down appetitive learning and reduced long-term memory specificity ( 7 ). Second, antagonistic effects can occur, where the combined effect of stressors is lower than expected based on the observation of the individual stressor effects. For instance, effects on hypopharyngeal gland size ( 8 ) in honeybees exposed to both, Varroa destructor mites and neonicotinoids effects were weaker as compared to honeybees exposed to only one of those stressors. And third, synergistic effects may be observed, where the combined effect is higher than expected based on the observation of the effects of the individual stressors. For instance, the simultaneous exposure to different pesticides, such as insecticide-fungicide mixtures at sublethal concentrations was shown to synergistically increase mortality in the honeybee, the bumblebee Bombus terrestris , and the solitary mason bee Osmia bicornis ( 9 ). It is assumed that the ergosterol-biosynthesis inhibiting fungicides inhibit a detoxification pathway that would also be needed to detoxify the insecticide ( 10 ), resulting in amplified negative effects when bees are confronted with both pesticides together. As synergistic effects of multiple stressors pose the greatest risk to bumblebee health and likely contribute to their decline, it is vital to compare other stressor combinations and gain an understanding of the underlying biochemical mechanisms that mediate negative effects. Currently, knowledge about the effects of stressor combinations other than those including pesticides is scarce. Bumblebees could be particularly sensitive to increased tropospheric ozone concentrations due to their high respiratory activity during flight ( 11 ). Tropospheric (near-surface) ozone is a secondary pollutant, as it is not directly produced and emitted but formed in the air. Anthropogenic pollution contains nitrogen oxides (NO x ; e.g. 12 ) which are for instance generated by combustion vehicles or during energy production from fossil fuels. Together with other gaseous airborne compounds (methane, hydrocarbons, carbon monoxide) the non-linear photochemistry of NO x yields ozone. Tropospheric ozone concentrations increase with the intensity of solar radiation and temperature ( 13 ). Climate change scenarios predict that ozone levels that are classified as harmful to human health will become increasingly common ( 14 ). Ozone is a highly reactive oxidant gas that can generate reactive oxygen species (ROS; 15 ) which could also harm insects. So far, in bees, ozone exposure (80 ppb – 200 ppb) was found to affect olfactory recall and detection, which is assumed to result from altered antennal activity ( 16 ). In honeybees, exposure to 80 ppb for one hour decreased the activity rate of the antioxidative enzyme superoxide dismutase ( 16 ). Another stressor that is steadily increasing in intensity is heat. For the year 2024, the annually averaged global mean near-surface temperature was 1.55 °C ± 0.13 °C above the 1850–1900 average ( 17 ), and the frequency and intensity of heat waves are also increasing ( 18 ). Acute heat stress can have various negative effects on insects, including increased mortality and decreased fertility (e.g. 19 ). While global warming is predicted to advance further, bumblebees could be particularly affected as they are generally considered cold-adapted ( 20 ). Hot temperatures are already contributing to declines of more cold-adapted bumblebee species ( 21 ). One stressor that has received less attention in multiple-stressor studies to date is microplastic (MP) pollution. MP refers to plastic particles smaller than 1000 µm ( 22 ) that are either intentionally added to products (i.e., primary MP) or created by the breakdown of larger plastic debris in the environment (i.e., secondary MP; 23 ). The presence of MP in the environment has become a cause of concern in recent decades. Due to increasing global plastic production and improper disposal, the presence of MP particles in the environment is steadily increasing ( 24 ). As most plastic waste is discarded within terrestrial ecosystems, organisms in these ecosystems might be particularly affected ( 25 ). Adverse health effects of MP on terrestrial organisms have already been observed in many studies: in terrestrial insects it was shown that MP-polluted food can increase mortality ( 26 ) and negatively affect growth and body size ( 27 ). Pollinators like bumblebees can get in contact with MP during foraging in MP polluted areas with contaminated nectar and pollen after atmospheric deposition of MP on flowers ( 28 ). Additionally, flight activity of bumblebees can further increase MP exposure. Due to friction with air, electrical charges accumulate on the body surface of bees ( 29 ) which in turn increases the adherence of airborne particulate pollutants (e.g. 30 ) such as MP. When transported back into colonies, MP is potentially ingested and distributed among worker bumblebees (e.g. 31 ). In nature, the three stressors increased tropospheric ozone concentrations, heat stress and MP pollution are likely to simultaneously affect bumblebees. The exact effects of these stressors on bumblebee health are not yet fully understood. In order to analyse the effects of the individual stressors and their combination, B. terrestris was exposed to each stressor individually as well as in all possible combinations of two and all three stressors together. In addition to assessing mortality, we quantitatively analysed the fat body proteome of B. terrestris . The proteomic profiles were compared across all treatment groups to identify biochemical mechanisms underlying the observed health effects. Furthermore, we measured relative fat body content as a proxy for metabolic costs and health status of the surviving bumblebees ( 32 ). Results Bumblebee mortality Throughout the 10-day exposure to ozone, heat, and MP as single stressors or in combinations of two or all three stressors, the mortality of bumblebee workers differed significantly between the different treatment groups (Log-Rank test, p = 3 · 10 -14 , χ 2 (df)= 78.4 (7), Fig. 1). In treatment groups without MP (individual stressors: H, O 3 ; combined stressors: HO 3 ), the mortality was not significantly different from the control (see Tab.1 for p values and Tab.S1 for test statistics; Fig. 1). All treatment groups including MP as a stressor, either MP alone, in combination with ozone or heat, or when all three stressors were combined, had a significantly higher mortality than the control and the treatment groups without MP (Tab.1, Tab.S1; Fig. 1). Furthermore, the treatment group with all three stressors combined (MPHO 3 ) had a significantly higher mortality compared to the treatment group with MP as an individual stressor (Tab. 1, Tab.S1; Fig. 1). For the combination of MP and heat and the combination of MP with ozone, the mortality was not significantly higher compared to MP individually (Tab. 1, Tab.S1; Fig. 1). Table 1: P-values from pairwise comparisons between the treatment groups using Log-Rank tests (degrees of freedom per comparison = 1, for χ 2 see Tab. S1) to detect significant differences in survival probability of bumblebees exposed to single stressors or combinations (ozone, heat, microplastic) for 10 days. Significant results (p < 0.05) are bold. C = control, O 3 = ozone, H = heat, MP = microplastic, HO 3 = heat + ozone, MPO 3 = microplastic + ozone, MPH = microplastic + heat, MPHO 3 = microplastic + heat + ozone. C O 3 H MP HO 3 MPO 3 MPH O 3 1.0000 H 1.0000 1.0000 MP 0.0061 0.0061 0.0061 HO 3 0.4039 0.4039 0.4039 0.0238 MPO 3 0.0001 0.0001 0.0001 0.2175 0.0005 MPH 2.3·10 -5 2.3·10 -5 2.3·10 -5 0.0686 8.8·10 -5 0.6813 MPHO 3 1.1·10 -5 1.1·10 -5 1.1·10 -5 0.0266 2.3·10 -5 0.4063 0.7804 Changes in the bumblebee fat body proteome Using a label-free LC-MS/MS approach, 59.616 peptides were quantified, which could be assigned to 5036 non-redundant proteins, with a false discovery rate (FDR) < 1% (see Data S2). Among the individual stressors, heat produced the strongest proteomic response with 193 proteins found to be altered in abundance (96 increased and 97 decreased; Fig. 2 B). MP followed with altered abundances of 104 proteins (63 increased and 41 decreased; Fig. 2 C). In comparison, ozone had the least impact altering the abundance of only 31 proteins (16 increased and 15 decreased; Fig. 2 A). The strongest response among the combined stressors was observed for heat combined with ozone, with 296 proteins changed in abundance (173 increased and 123 decreased; Fig. 2 D). The combination of MP with ozone resulted in 200 proteins altered in abundance (117 increased and 83 decreased; Fig. 2 E) exceeding the summed effects of the two individual stressors (O 3 : 31; MP: 104; see Fig. 2 A & C). In contrast, the combination of the two stressors that individually induced most changes in protein abundances, heat and MP, altered a total of only 120 proteins (80 increased and 40 decreased; Fig. 2 F). The exposure to all three stressors simultaneously (MP, O₃ and H) did not result in the greatest number of proteins changed in abundance, with 164 proteins altered (90 increased, 74 decreased; Fig. 2 G). A variety of proteins associated with immune responses, tissue damage responses, heat responses, responses to toxic substances, oxidative stress responses, and metabolic processes, were differentially abundant in bumblebees after exposition to ozone, heat, and MP individually and combined, in comparison to untreated controls (see Fig. 3; for a full list of all comparisons see Data S3). Among the individual stressors, changes in the abundance of proteins associated with immune responses were most prominent in MP treatment, while changes in the abundance of proteins associated with metabolic processes were most prominent after heat treatment. The ozone treatment was the only single stressor treatment in which the abundance of catalase, a protein directly associated to ROS-responses, was increased in abundance. In multiple stressor treatments, we found that the interaction of several stressors led to proteome changes in areas that were not affected by the corresponding stressors individually (e.g. compare O 3 , H, and HO 3 ). Notably, proteins linked to immune responses were particularly affected by heat combined with ozone, MP individually and in combination with other stressors, especially MP and ozone, while for heat and ozone individually these effects were less prominent. Furthermore, the abundance of several phospholipase A1 and A2 isoforms showed increased protein abundance for treatments including heat. Strikingly, when all three stressors were present, a significant abundance alteration of the phospholipases was not detected. On the other hand, MP decreased phospholipase abundance, an effect further exacerbated by ozone. In addition, proteins associated with carbohydrate metabolism, including trehalase, alpha-amylase, the glycogen debranching enzyme and several alpha-glucosidase isoforms were less abundant in all treatments except ozone individually. This was particularly pronounced in multiple stressor treatments. Notably, an increase in the abundance of apoptosis-inducing factor 3 was observed exclusively for MP individually and combined with O₃ with and without heat exposures. Changes in the bumblebees’ relative fat body content Even though differences in the relative fat body content were detected among the treatment groups (Kruskal-Wallis rank sum test, p = 0.03, χ 2 = 15.31, df = 7), the results were visually not as pronounced as for the mortality (Fig. 4). We only found the relative fat body content to be significantly lower in the treatment group with MP in combination with ozone, both compared to the control and compared to MP alone (Fig. 4, Tab. 2, Tab. S4). Table 2: P-values for the pairwise comparisons between the treatment groups using Log-Rank test (degrees of freedom per comparison = 1, for z-values see Tab. S4) to detect significant differences in relative fat body content of bumblebees exposed to multiple stressors (ozone, heat, microplastic) for 10 days. Significant results (p < 0.05) are bold. C = control, O 3 = ozone, H = heat, MP = microplastic, HO 3 = heat + ozone, MPO 3 = microplastic + ozone, MPH = microplastic + heat, MPHO 3 = microplastic + heat + ozone. C O 3 H MP HO 3 MPO 3 MPH O 3 0.629 H 0.629 0.995 MP 0.995 0.629 0.629 HO 3 0.629 0.995 0.995 0.629 MPO 3 0.047 0.082 0.082 0.047 0.082 MPH 0.410 0.629 0.629 0.410 0.629 0.406 MPHO 3 0.135 0.284 0.284 0.135 0.284 0.743 0.629 Discussion In our study, we exposed groups of B. terrestris workers to a set of stressors that bumblebees are likely simultaneously exposed to in their natural environment: increased tropospheric ozone concentrations, heat stress, and MP contaminated food. We exposed the bumblebees to these stressors either individually, in combinations of two or all three stressors. MP exposure had the greatest effects on bumblebee health, affecting them significantly at both, the sublethal and lethal level. MP was the only single stressor that increased bumblebee mortality. Furthermore, bumblebee mortality was significantly increased by all stressor combinations including MP. In contrast, ozone and heat individually and their combination did not increase bumblebee mortality, and affected bumblebee health only on the sublethal level. The fat body proteome was differentially altered in all treatments, with different patterns. Additionally, the relative fat body content was significantly lower only in bumblebees treated with the combination of MP and ozone. Ozone exposure induces oxidative stress response in bumblebees Exposure to ozone individually did not influence bumblebee mortality. On the sublethal level however, we found an increased abundance of catalase in the fat body proteome, a change that occurred exclusively in the ozone treatment. Catalase is an important antioxidant enzyme that counteracts ROS-induced oxidative stress and associated damage (e.g. 33 ). Ozone is known to be a strong oxidant that directly induces the production of ROS (e.g. 15 ). In insects, the exposure to increased ozone concentrations has been shown to result in increased activity of antioxidant enzymes, which are important for neutralizing ROS and preventing damage from oxidative stress (e.g. 16, 34 ). Salem et al. ( 34 ) found catalase activity to increase in the common house mosquito Culex pipiens after ozone exposition, supporting our finding. Beyond antioxidant enzymes, we also observed other changes in the fat body proteome that exclusively occurred in the ozone treatment among the single stressor treatments. For example, a protein of the short-chain dehydrogenase/reductase family 16 C, and the phospholipase A2 (A0A9BJS26) was decreased in abundance. These two proteins are important in metabolic processes and signalling (short-chain dehydrogenase/reductase family 16 C members: 35 ; phospholipase A2: 36 ). This suggests that ozone exposition may cause a dysregulation of metabolic processes and signalling in bumblebees and negatively affect insect health beyond oxidative damage by ROS. Since there was no significant reduction in the relative fat body content, the effects of increased ozone concentrations on bumblebee health appear to be limited to minor sublethal effects, at least within the exposure period and the concentration of about 120 ppb used in our experiment. Heat stress induces changes in bumblebee metabolism Similar to ozone, heat did not affect bumblebee mortality when applied individually. On the sublethal level, however, heat induced changes in the fat body proteome, including alterations in the abundance of multiple proteins associated with metabolic processes. In insects, heat stress has previously been recorded to induce changes in the metabolism (e.g. 37 ). Our proteomic data suggest a switch in the use of energy sources from carbohydrate reserves to lipid reserves under heat stress. While abundances of proteins associated with energy mobilization from carbohydrates were reduced (trehalase: 38 , alpha-1,4 glucan phosphorylase: 39 , glycogen debranching enzyme: 40 ) abundances of proteins associated with phospholipid digestion were mostly increased (phospholipase A1 (A0A9B0C041, A0A9B0F3T4, A0A9B0F5E1): 41 ). In line with our results, an increased use of lipid reserves under heat stress has been observed in insects before (e.g. in Drosophila melanogaster , 42 ). However, the putative switch to a more lipid-based energy metabolism was not reflected in a reduction in relative fat body content in this treatment. That said, it should be noted that in our experimental design, the bumblebees had lower energy requirements because their ability and need to move was restricted. In the heat-only treatment, we found no increase in the abundance of heat shock proteins, that are important for maintaining cell homeostasis by protecting substrate proteins from e.g. denaturation due to heat or other stressors (e.g. 43 ). However, it must be considered, that the bumblebees were not exposed to short very hot extreme temperatures but to rather mild chronical heat stress. With 33 °C, the temperature was about 3 °C above the optimal nest temperature of B. terrestris (ranging from 28 °C to 30 °C, e.g. 44 ), which could have been insufficient to induce heat shock proteins in adult workers. MP ingestion increases bumblebee mortality MP was the only single stressor that significantly increased bumblebee mortality. This finding is in line with previous studies that observed increased insect mortality after ingestion of MP of various polymer types, sizes, and concentrations (e.g. 45 : Apis mellifera , PE-spheres, 100 µm, 10 5 particles/ml, for 15 d; 26 : D. melanogaster , PS-spheres, 1.8 – 2.2 µm, 0.5 µg/ml, 14 d, males especially sensitive). Furthermore, the analysis of the fat body proteome revealed that in the MP treatment the abundances of multiple proteins important for immune responses, responses to toxic substances, metabolic processes, tissue damage responses and heat response were altered. These changes were not observed in the ozone- and heat-only treatments. The underlying mechanisms of increased mortality and sublethal adverse health effects after MP ingestion are not fully understood, but are thought to be driven by several factors, including chemical and mechanical or physical effects of the MP particles. Besides the polymer itself, plastics usually contain a multitude of toxic substances. Even additive-free plastics, like the LDPE we used, can contain residual monomers, solvents, catalysts from their synthesis or non-intentionally added substances (NIAS) like degradation products and impurities from the manufacturing process ( 46 ). NIAS are not chemically bound to the polymer matrix and can leach from the plastic ( 46 ). After ingestion of LDPE‑contaminated food, these leached NIAS may adversely affect bumblebee health. In line with the possible release of toxic substances from the LDPE MP, we found some cytochromes P450, which are important in detoxification processes (e.g. 47 ), to be more abundant in the fat body proteome of bumblebees from the MP treatment, but not in the other single stressor treatments. This suggests chemical toxicity to be one of the possible mechanisms explaining the adverse effects on insect health induced by MP. In addition to health effects mediated by toxic chemical substances, the MP particles themselves could mechanically harm insects. For instance, an accumulation of MP particles could result in a blocking of the gut system and entail lower intake of nutrients (e.g. 48 ) or induce tissue damage (e.g. 49 ). Our fat body proteome results are in line with this assumption. Among the single stressor treatments, we found exclusively for MP increased abundances of some proteins associated with tissue damage responses such as phenoloxidase-activating factor 2 (e.g. 50 ), transferrin (e.g. 51 ), ferritin light chain and ferritin heavy chain (e.g. 51 ), and the protein windpipe as an important regulator of pathways involved in tissue replacement after damage of midgut epithelium ( 52 ). Furthermore, we found (exclusively in the MP-only treatment) increased abundances of two proteins associated with the invertebrate humoral immune response, abaecin and hymenoptaecin (e.g. 53 ). These proteins are commonly associated with responses to pathogen challenges (e.g. 54 ). However, changes in their abundances in response to non-infectious stress such as heat stress (e.g. Apis cerana & A. mellifera ; 55 ), aseptic wounding (e.g. D. melanogaster ; 56 ), or exposure to pesticides (e.g. Bombus impatiens ; 57 ) have been observed before. Therefore, it is possible that their abundances could also change after MP ingestion, triggered either by toxic substances, similar to the reaction to pesticides, or by tissue damage caused by the particles themselves. Activated immunity under such abiotic stress is assumed to prevent infection under stressful conditions ( 55 ). Our findings on the fat body proteome support both, chemical and mechanical mechanisms as possible explanations for the adverse health effects after MP ingestion. We suggest further studies to better understand how negative health effects of MP are mediated mechanistically. MP exacerbates the negative health effects of ozone and heat We found MP to exacerbate the negative health effects of ozone and heat. When applied individually, ozone and heat did not increase bumblebee mortality, but only adversely affected bumblebee health at the sublethal level. However, in combination with MP, bumblebee mortality was increased beyond the effect caused by MP alone. Therefore, the combination with MP appears to amplify the detrimental health effects of ozone and heat to a lethal level suggesting a synergistic effect. This synergistic effect was strongest for the combination of all three stressors. A conceivable underlying mechanism could be the inhibition of protective responses to one stressor by another. Our results for the fat body proteome support this scenario. We found the abundance of the protein lethal(2) essential for life (A0A9B2JR06), a heat shock(-related) protein (e.g. 58 ), to be decreased after MP exposure. Therefore, MP exposure could make bumblebees more susceptible to heat damage, supporting the proposed underlying mechanism. Following the pattern observed for bumblebee mortality, we would also expect the strongest adverse health effects at the sublethal level in the treatment combining all three stressors. Consequently, we would have anticipated the lowest relative fat body content in this treatment. In contrast however, the relative fat body content was reduced in bumblebees exposed to the treatment combining ozone and MP exclusively. However, the observed pattern was most likely superimposed by a survivorship bias (e.g. 59 ), because only individuals that survived the 10-day exposure were included in measurements of sublethal effects. Since mortality rates differed between the treatments, selection for the strongest individuals (the survivors) differed among treatments. Survivors may have had a higher body fat content per se, thereby masking a mutual exacerbation of sublethal effects of combined stressors on the relative fat body content. The higher the mortality rate, the more pronounced this bias is. In conclusion, the exposure of B. terrestris workers to the three naturally concurrent stressors, increased ozone concentrations, heat stress, and MP pollution, either alone or in combination, affected bumblebee mortality, fat body proteome and relative fat body content. The single stressors resulted in different proteomic alterations, suggesting different modes of action of the single stressors. While ozone induced changes in the abundance of proteins related to oxidative stress responses, heat stress led to alterations of proteins involved in metabolic processes, and MP induced abundance changes associated with tissue damage responses and detoxification reactions, amongst others. For stressor combinations, especially those including MP, negative health effects were synergistic. We hypothesise that resistance to one stressor (e.g. heat) may be reduced by another stressor (e.g. MP) as an underlying mechanism. Synergistic effects were particularly evident for bumblebee mortality. While mortality was not affected by ozone, heat, and their combination alone, the addition of MP synergistically exacerbated their negative health effects to such an extent, that they resulted in an increased mortality. Our findings suggest, that even if the effects of ozone, heat and MP are not yet serious under current environmental conditions, they may pose a serious health risk in the future, especially under the consideration of the progressive accumulation of MP in the environment, rising temperatures and the resulting increase in ozone levels. Materials and Methods Experimental design Bumblebee husbandry Eight Bombus terrestris colonies were ordered from Biobest (Westerlo, Belgium). They were kept in their delivery boxes in a climate chamber at constant 26 °C and 70 % atmospheric moisture under an inverted 12:12 h dark:light cycle. The colonies were fed three times per week with approximately 10 grams of pollen (Imkerpur, Osnabrück, Germany) and sugar water [1:1 ratio of water to Apiinvert (Südzucker AG, Mannheim, Germany)] ad libitum . Production and characterization of microplastic We used irregularly shaped low-density polyethylene (LDPE) fragments for the MP-exposure via food. We chose LDPE, since this polymer is one of the most common plastic wastes, and frequently used in agriculture (e.g. as mulching film; see 60 and citations herein). To produce the LDPE fragments, LDPE granules (Lupolen 1800P, Lyondell Basell, Bayreuth, Germany) were milled (centrifugal mill ZM300, RETSCH GmbH, Haan, Germany; rotor: 24Z; sieve: distance sieve 200 µm) and subsequently sieved with an air jet sieve (e200 LS, Hosokawa Alpine AG, Augsburg, Germany; sieves: 75µm and 20µm) to achieve the particle size fraction of 20 – 75 µm we worked with. In this size class, the number particle size distribution showed 50 % of the particles had a diameter (d 50 ) smaller than 25.75 μm (d 10 = 15.86 μm, d 90 = 55.77 μm; Fig. S5). We used this size class, as it overlaps extensively with the size of pollen of plants that B. terrestris pollinates ( 61, 62 ). This size overlap guarantees easy ingestion of the MP with food during the experiment. The particle size-distribution was determined by a Microtrac Sync particle analyser (Microtrac RETSCH GmbH, Haan, Germany; Fig. S5). Generation of ozone For ozone generation, ambient air was filtered and dehumidified using an air feed pump (Ansyco, analytische Systeme und Componenten GmbH, 76131 Karlsruhe, Germany; see Fig. S6: 1-2), which also created a regulated gas flow of four litres per minute. To regulate the amount of ozone produced, the gas flow was divided into two air streams by a branching with rotary control (see Fig. S6: 3) and one of them was exposed to a UV lamp (LSP035 pen-ray lamp (Hg/Ar), L.O.T.-Oriel GmbH & Co. KG, 64293 Darmstadt, Germany, see Fig. S6: 4) to generate ozone with the radiation. This ozone-enriched air was subsequently mixed again with the rest of the purified air and led into a 12-litre glass-tank (30 cm x 20 cm x 20 cm; see Fig. S6: 5), that was sealed air-tight with an acrylic glass cover (polymethyl methacrylate, 210 mm x 297 mm x 2 mm) wrapped in a sheet of 50 µm thick UV-transparent fluorinated ethylene propylene film (200A FEP100, The Chemours Company TM ) and body sealant (Teroson® RB IX, grey, Henkel AG & Co. KGaA, 40191 Düsseldorf, Germany; see Fig. S6: 6). By regulating the amount of air passing the UV lamp via the branching with rotary control, the ozone concentration in the glass tank was controlled. The ozone concentration was constantly tracked using an ozone analyser (Model 49i, range: 0-0.05 – 1.0 ppm, Ansyco, analytische Systeme und Componenten GmbH, 76131 Karlsruhe, Germany; see Fig. S6: 8), which extracted air from the glass tank (flow rate: 1.5 L/min) for analysis. We used environmentally relevant ozone concentrations of about 120 ppb (measured values: 127.21 ppb ± 4.91 ppb) as they are reached during daily peaks of hot and sunny periods ( 63 ). Treatments without ozone as a stressor were provided with purified air only, as the UV lamp was turned off. Multiple stressor exposition of B. terrestris workers B. terrestris workers were picked randomly from the colonies the day before the experiment. They were individually put into cages (Nicot®-Queen cage, Nicotplast SAS, Maisod, France) attached to 10-ml syringes (Injekt® Solo, B Braun Melsungen AG, 34212 Melsungen, Germany) and fed with sugar water from the syringes for acclimatization to the experimental conditions. The workers were randomly divided into eight groups of 48 individuals each, resulting in 384 individuals in total. Care was taken to ensure that each group contained six individuals from each of the eight source colonies. Each group of 48 individuals was assigned to one of the following treatments: control (C), the treatments with individual stressors, microplastic (4.25 % LDPE in the food, MP), heat (33 °C constantly, H), and ozone (~120 ppb for two hours per day, O 3 ), the treatments with two stressors combined, microplastic and heat (MPH), microplastic and ozone (MPO 3 ), and heat and ozone (HO 3 ), and the treatment with all three stressors combined, microplastic, heat and ozone (MPHO 3 ). The chronic exposure to the stressors lasted for ten days. Throughout this period, the individuals were provided with water (4 ml) and small portions (0.8 g ± 0.1 g) of sucrose-based food dough [based on Apifonda, (Südzucker AG, Mannheim, Germany)] containing the LDPE MP. We calculated the concentration of LDPE added to the food dough (in w/w) to correspond to a concentration of 4.25 % of LDPE (w/V) in sugar water (1:1, Apiinvert:H 2 O, V/V), the standard food for bumblebees in most experimental set ups with individuals (e.g. 64, 65 ). As one kilogram of the food dough contains about twice as much sugar as one litre of the sugar water, we used about twice the amount of LDPE (8.8 %, w/w, for detailed calculation see Tab. S7) to prepare the MP contaminated food dough. With 4.25 %, we selected a MP concentration in a range that has been used previously in studies on MP effects on insects (e.g. 45 for honeybees: up to 10 5 PE-spheres with a diameter of 100 µm per ml of honey equals ≈ 51 g/L ≈ 5 % w/w; calculation in Tab. S8). In the environment such concentrations are currently only found in exceptional situations (e.g. reviewed by 66 : up to 10 % w/w of MP from tire abrasion at roadside sediments). To obtain the right consistency, the food dough was additionally mixed with powdered sugar (15 % by weight in treatments without and 6.2 % by weight in treatments with MP). We chose food dough as sugar source over sugar water, to ensure a constant and uniform provisioning of MP particles with food. In sugar water MP particles could float to the surface due to their lower density and a surfactant would be necessary to suspend the particles. The food dough and water were refreshed every three days to ensure ad libitum supply. Additionally, to prevent the food dough from drying out and therefore becoming inaccessible as food source, each cage was sprayed daily with 2 ml of deionised water. For exposure to heat or the control temperature, the bumblebees were kept in two identical climate cabinets (Type 3500, Rumed® Rubarth Apparate GmbH, 30880 Laatzen, Germany) at 60 % to 80 % relative humidity. The temperature was kept constant at 27 °C for all treatment groups without heat as a stressor, and 33 °C for all treatment groups with heat as a stressor. Prior to the start of the experiment the temperature for groups with heat as a stressor was increased gradually from 27 °C to 33 °C, with a heating rate of 1 °C per hour to acclimatize the bumblebees to the new temperature. Throughout the experiment the individuals were positioned in the climate cabinets randomly and rotated daily. Ozone/control exposure was conducted daily for two hours in the fumigated glass tank, which was positioned in an incubator (Stuart® orbital incubator SI500, Bibby Scientific Limited, Staffordshire, United Kingdom) to keep the experimental temperatures. The required relative humidity was achieved in the glass tank using four pieces of cotton wool balls weighing four grams each (100 % viscose), each soaked in 30 ml of deionised water. Relative humidity and temperature in the glass tank were tracked throughout the exposition using a thermohygrometer (ClimaTemp, Bresser GmbH, 46414 Rhede, Germany). Prior to the two hours of exposure time, the parameters were allowed to stabilize for 30 minutes, during which the animals were already in the closed glass tank. The two-hour exposure time was selected to mimic natural daily peaks in ozone-concentrations. During the gas exposure the bumblebees were stacked within the glass tank in their individual cages. As the individuals differed in distance to the ozone gas inlet, the order of stacking was changed randomly for each exposition. At the end of the experiment, the individuals were evenly (in terms of source colony and number of repetitions) divided into two groups per treatment. One group was assigned to measure the fat body content and one for analysing the proteome of the fat body. All individuals were anesthetized on dry ice. Individuals for fat body analyses were then euthanized on dry ice and subsequently stored frozen at -20 °C until analysis. For the proteome analysis, the anesthetized individuals were immediately snap frozen with liquid nitrogen and then stored at -80 °C until analysis. Proteome analysis Proteomic analysis was conducted on fat body tissue of B. terrestris . For this analysis, the fat body was dissected from bumblebee bodies within five minutes after thawing frozen specimen for approximately two minutes at room temperature. All collected fat body tissue per individual was transferred to a separate autoclave-sterilised 0.5 ml micro tube, snap-frozen in liquid nitrogen and again stored at -80 °C upon further analysis. For each treatment group and for the control, the fat body of one individual was randomly selected from each of the eight colonies, resulting in a sample size of n = 8 independent replicates per treatment. Dissected frozen fat bodies were thawed and lysed in 40 µl lysis buffer (8M Urea, 50 mM ammonium hydrogen carbonate) followed by sonication using a Sonopuls HD3200 cup resonator (BANDELIN electronic GmbH & Co. KG, Berlin, Germany; 10 seconds pulse, 20 seconds rest, 12 cycles) and then homogenized using QIAshredder (Qiagen, Hilden, Germany) device (20817x g, 1 min). Protein concentrations were determined using the Pierce 660 nm Protein Assay (Thermo Fisher Scientific, Rockford, IL, USA). Proteins were reduced in 4 mM dithiothreitol (DTT) and 1.8 mM tris(2-carboxyethyl)phosphine at 56 °C for 30 min and then alkylated in 8 mM iodoacetamide at room temperature for 30 min in the dark. The reaction was quenched by adjusting the DTT concentration to 10 mM at RT for 15 min in the dark. After reduction and alkylation, all samples were sequentially digested, first with Lys-C (enzyme-to-protein ratio 1:100, 4 h at 37 °C, FUJIFILM Wako Chemicals Europe GmbH, Neuss, Germany) followed by trypsin (enzyme-to-protein ratio 1:50, 18 h at 37 °C, Promega, Madison, WI, USA) after adjusting the urea concentration to 1 M. The digestion was stopped by adding formic acid (FA) to a final concentration of 1%. Peptides were dried in a vacuum concentrator and subsequently reconstituted in 0.1% FA. LC-MS/MS analysis was performed on a nanoElute 2-LC system connected to a timsTOF HT mass spectrometer (both Bruker Daltonics Inc., Fremont, CA, USA), operated in the data-independent acquisition (DIA) mode. 750 ng of peptides were first loaded onto a trap column (PepMap Neo trap column (300 µm× 5 mm, 5 µm particles, C18, Thermo Fisher Scientific, Waltham, MA, USA)) and separated on a PepSep Ultra C18 25 cm x 75 µm, 1.5 µm (Bruker Daltonics Inc., Fremont, CA, USA), at 250 nL/min with a 25 min gradient of 2-25% of solvent B followed by a 12 min increase to 37%. Solvent A consisted of 0.1% FA in water and solvent B of 0.1% FA in acetonitrile. The mass spectrometer was run in the dia-PASEF mode using 21 25 m/z wide windows and ion mobility ramps between 0.85 and 1.27 1/k0. The sample order was randomized, and carryover was minimized by running blanks between samples. Protein identification and peptide quantification was carried out with DIA-NN (v2.2.0; 67 ). The B. terrestris database (UniProt Reference Proteome UP000835206, retrieval date:28.02.2025) alongside the built-in contaminants fasta file was used. Due to limited annotation in the database, protein selection focused on well-annotated entries. Representative proteins were manually selected based on the following criteria: (i) consistent identification across multiple pairwise comparisons, and (ii) functional relevance to the respective functional groups associated with the applied stressors. The full list of proteins significantly altered in abundance, all differentially altered proteins and a list of all identified proteins can be found in the supplementary material (Data S9, Data S3, and Data S2). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE ( 68 ) partner repository with the dataset identifier PXD071780. Fat body assays To gain insights into the status of energy storage and indications of immune and detoxification reactions (e.g. 32 ), we analysed the relative fat body content of treated bumblebees. Therefore, the bumblebee workers (10–23 per treatment, depending on how much the number of repetitions was reduced due to mortality) were thawed and their abdomen separated from the rest of the body. The sternites one to five were cut open ventrally. Each abdomen was individually placed into a 5 ml glass vial with snap lid and dried for five days in a drying cabinet at 70 °C. After drying, the abdomens were weighed using a precision scale (VWR SM1265Di, d = 0.01 mg, VWR International, Leuwen, Belgium) and then covered in 5 ml petroleum ether (boiling range: 40 °C – 60 °C, containing ~ 2 % n-Hexane, Fisher Scientific, Loughborough, United Kingdom), which was exchanged daily for three days to dissolve the fat body. After this period, the petroleum ether was removed using a glass pipette, and the abdomens were dried again for five days (drying cabinet, 70 °C). The abdomens were then weighed again. The relative fat body content for each individual was determined as follows: (1) Statistical analysis The analyses of the mortality (for mortality data see Data S10) and the relative fat body content (for relative fat body content data see Data S11) were conducted in R version 4.4.1 ( 69 ). To compare the survival between the treatments (48 replicates were used per treatment), we used a Kaplan-Meier estimator (function: survfit , R package: survival ; 70 ). We visualised the survival curves with the function ggsurvplot from the survminer R package ( 71 ). To analyse the survival data, we applied a Cox-proportional-hazards-model (function: coxph , package: survival ; 70 ) and used Schoenfeld residuals (function: cox.zph , package: survminer ; 71 ) to test the assumptions of the model. To test for overall differences between the treatments, we applied a Log-Rank test (function: survdiff , package: survival ; 70 ). Additionally, we conducted pairwise comparisons among treatments, using a Log-Rank test (function: pairwise_survdiff , package: survminer ; 71 ). To account for multiple testing, p-values were adjusted following Benjamini & Hochberg ( 72 ). For analysing and visualising the results of the fat body assays, we tested our data for deviance from a normal distribution (function: shapiro.test , package: stats ; 69 ) and homogeneity of variance (function: leveneTest , package: car ; 73 ). Since neither normality nor variance homogeneity assumptions were met, we finally used a Kruskal Wallis rank sum test (function: kruskal.test , package: stats ; 69 ) to test for overall differences in the relative fat body content among treatments, followed by pairwise comparisons using a Dunns post-hoc-test (function: dunn_test , package: rstatix ; 74 ). Again, p-values were adjusted following Benjamini & Hochberg ( 72 ) to correct for multiple testing. To calculate the means of the individual treatments, we used the aggregate function of the stats package ( 69 ). We visualised the data with violin plots (function: ggplot , package: ggplot2 ; 75 ). The statistical evaluation and bioinformatics of the fat body proteome were performed using R Version 4.5.1 ( 76 ). The DIA-NN main report was filtered according to recommendations from the developers ( 77 ). The FDR confidence was set to < 1%, and proteins were filtered for a minimum of two unique peptides. To identify differentially abundant proteins, MS-EmpiRe ( 78 ) was used. To account for multiple testing, p-values were adjusted following Benjamini & Hochberg ( 72 ; FDR < 0.05). Declarations Acknowledgments We kindly acknowledge Daniel Wagner of the subproject Z01 of the CRC 1357 Microplastics for providing and characterizing the used microplastic particles. Funding: This study was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) – SFB 1357 Mikroplastik – Project Number 391977956. This study was supported by the Studienstiftung des deutschen Volkes and the Marianne-Plehn program (MPP), through the PhD and the MPP scholarship of Gwen Büchner. Publishing costs of this study were funded by the Open Access Publishing Fund of the University of Bayreuth. Open Access funding enabled and organized by Projekt DEAL. Author contributions: Author contributions follow the CRediT model: Conceptualization: GK, MMR, AN, TF, HF Methodology: GK, MMR, FK, AS, AN, TF, HF Investigation: GK, MMR, MMM, JBS, FK, AS, TF Visualization: GK, MMR Supervision: AN, TF, HF Writing—original draft: GK, MMR, TF, HF Writing—review & editing: GK, MMR, MMM, JBS, FK, AS, AN, TF, HF Competing interests: Authors declare that they have no competing interests. Data and materials availability: All data are available in the main text or the supplementary materials. Data and code for all analyses except proteomics are submitted with this manuscript at first submission. Upon acceptance of the manuscript all data and code will be made publicly available online on Zenodo under: Kühn, G. (2026). Negative effects of increased ozone concentrations and heat stress on bumblebees are exacerbated by microplastics [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18429390 Proteomics data are available via ProteomeXchange with the identifier PXD071780 at http://www.ebi.ac.uk/pride . References J. Ollerton, Pollinator diversity: distribution, ecological function, and conservation. Annu. Rev. Ecol. Evol. Syst. 48 , 353–376 (2017). H. H. W. Velthuis, A. van Doorn, A century of advances in bumblebee domestication and the economic and environmental aspects of its commercialization for pollination. Apidologie 37 , 421–451 (2006). S. A. Cameron, B. M. Sadd, Global trends in bumble bee health. Annu. Rev. Entomol. 65 , 209–232 (2020). D. L. Wagner, Insect declines in the anthropocene. Annu. Rev. Entomol. 65 , 457–480 (2020). D. Goulson, E. Nicholls, C. Botías, E. L. Rotheray, Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science 347 , 1255957 (2015). R. B. Schäfer, J. J. Piggott, Advancing understanding and prediction in multiple stressor research through a mechanistic basis for null models. Glob. Chang. Biol. 24 , 1817–1826 (2018). C. Monchanin, E. Drujont, J.-M. Devaud, M. Lihoreau, A. B. Barron, Metal pollutants have additive negative effects on honey bee cognition. J. Exp. Biol . 224 (2021). S. Bruckner, L. Straub, P. Neumann, G. R. Williams, Negative but antagonistic effects of neonicotinoid insecticides and ectoparasitic mites Varroa destructor on Apis mellifera honey bee food glands. Chemosphere 313 , 137535 (2023). F. Sgolastra, P. Medrzycki, L. Bortolotti, M. T. Renzi, S. Tosi, G. Bogo, D. Teper, C. Porrini, R. Molowny-Horas, J. Bosch, Synergistic mortality between a neonicotinoid insecticide and an ergosterol-biosynthesis-inhibiting fungicide in three bee species. Pest Manag. Sci. 73 , 1236–1243 (2017). M. R. Berenbaum, R. M. Johnson, Xenobiotic detoxification pathways in honey bees. Curr. Opin. Insect Sci. 10 , 51–58 (2015). R. K. Suarez, Energy metabolism during insect flight: biochemical design and physiological performance. Physiological and Biochemical Zoology 73 , 765–771 (2000). I. S. Mudway, F. J. Kelly, Ozone and the lung: a sensitive issue. Mol. Asp. Med. 21 , 1–48 (2000). S. Brönnimann, U. Neu, Weekend-weekday differences of near-surface ozone concentrations in Switzerland for different meteorological conditions. Atmos. Environ. 31 , 1127–1135 (1997). E. Hertig, Health-relevant ground-level ozone and temperature events under future climate change using the example of Bavaria Southern Germany. Air Qual. Atmos. Health. 13 , 435–446 (2020). V. Bocci, G. Valacchi, F. Corradeschi, C. Aldinucci, S. Silvestri, E. Paccagnini, R. Gerli, Studies on the biological effects of ozone: 7. Generation of reactive oxygen species (ROS) after exposure of human blood to ozone. J. Biol. Regul. Homeost. Agents 12 , 67–75 (1998). F. Démares, L. Gibert, B. Lapeyre, P. Creusot, D. Renault, M. Proffit, Ozone exposure induces metabolic stress and olfactory memory disturbance in honey bees. Chemosphere 346 , 140647 (2024). WMO, State of the global climate 2024 (World Meteorological Organization, Switzerland, ed. 1368, 2025). S. Legg, IPCC, 2021: Climate Change 2021 - the Physical Science basis. Interaction 49 , 44–45 (2021). K. Sales, R. Vasudeva, M. J. G. Gage, Fertility and mortality impacts of thermal stress from experimental heatwaves on different life stages and their recovery in a model insect. R. Soc. Open Sci. 8 , 201717 (2021). J. E. Ogilvie, J. R. Forrest, Interactions between bee foraging and floral resource phenology shape bee populations and communities. Curr. Opin. Insect Sci. 21 , 75–82 (2017). P. Soroye, T. Newbold, J. Kerr, Climate change contributes to widespread declines among bumble bees across continents. Science 367 , 685–688 (2020). International Standard ISO 24187, Principles for the analysis of microplastics present in the environment (ed. 60, 2023). S. Manzoor, N. Naqash, G. Rashid, R. Singh, Plastic material degradation and formation of microplastic in the environment: a review. Mater. Today Proc. 56 , 3254–3260 (2022). R. C. Thompson, W. Courtene-Jones, J. Boucher, S. Pahl, K. Raubenheimer, A. A. Koelmans, Twenty years of microplastic pollution research-what have we learned? Science 386 , eadl2746 (2024). A. A. Horton, A. Walton, D. J. Spurgeon, E. Lahive, C. Svendsen, Microplastics in freshwater and terrestrial environments: evaluating the current understanding to identify the knowledge gaps and future research priorities. Sci Total Environ. 586 , 127–141 (2017). S. El Kholy, Y. Al Naggar, Exposure to polystyrene microplastic beads causes sex-specific toxic effects in the model insect Drosophila melanogaster . Sci. Rep. 13 , 204 (2023). S. Shah, M. Ilyas, R. Li, J. Yang, F.-L. Yang, Microplastics and nanoplastics effects on plant-pollinator interaction and pollination biology. Environ. Sci. Technol. 57 , 6415–6424 (2023). D. Sheng, S. Jing, X. He, A.-M. Klein, H.-R. Köhler, T. C. Wanger, Plastic pollution in agricultural landscapes: an overlooked threat to pollination, biocontrol and food security. Nat. Commun. 15 , 8413 (2024). Y. Vaknin, S. Gan-Mor, A. Bechar, B. Ronen, D. Eisikowitch, The role of electrostatic forces in pollination. in Pollen and Pollination , A. Dafni, M. Hesse, E. Pacini, Eds. (Springer Vienna, Vienna, s.l., 2000), pp. 133–142. J.-M. Bonmatin, C. Giorio, V. Girolami, D. Goulson, D. P. Kreutzweiser, C. Krupke, M. Liess, E. Long, M. Marzaro, E. A. D. Mitchell, D. A. Noome, N. Simon-Delso, A. Tapparo, Environmental fate and exposure; neonicotinoids and fipronil. Environ. Sci. Pollut. Res. Int. 22 , 35–67 (2015). A. M. Alma, G. S. de Groot, M. Buteler, Microplastics incorporated by honeybees from food are transferred to honey, wax and larvae. Environ. Pollut. 320 , 121078 (2023). E. L. Arrese, J. L. Soulages, Insect fat body: energy, metabolism, and regulation. Annu. Rev. Entomol. 55 , 207–225 (2010). M. Corona, G. E. Robinson, Genes of the antioxidant system of the honey bee: annotation and phylogeny. Insect. Mol. Biol. 15 , 687–701 (2006). H. H. A. Salem, S. H. Mohammed, R. I. Eltaly, E. M. Elqady, E. El-said, K. H. Metwaly, Effectiveness and biochemical impact of ozone gas and silica nanoparticles on Culex pipiens (Diptera: Culicidae). Sci. Rep. 14 , 19182 (2024). K. L. Kavanagh, H. Jörnvall, B. Persson, U. Oppermann, Medium- and short-chain dehydrogenase/reductase gene and protein families: the SDR superfamily: functional and structural diversity within a family of metabolic and regulatory enzymes. Experientia 65 , 3895–3906 (2008). M. Kilaso, C. Tipgomut, N. Sanguankiattichai, C. Teerapakpinyo, C. Chanchao, Expression and DNA methylation of phospholipase A2 in Thai native honeybees (Hymenoptera: Apidae). Russ. J. Dev. Biol. 47 , 190–201 (2016). J. F. Gillooly, J. H. Brown, G. B. West, M. van Savage, E. L. Charnov, Effects of size and temperature on metabolic rate. Science 293 , 2001, 2248–2251 (2001). J. Qin, F. Liu, J. Wu, S. He, M. Imran, W. Lou, H. Li-Byarlay, S. Luo, The molecular characterization and gene expressions of trehalase in bumblebee, Bombus lantschouensis (Hymenoptera: Apidae). Sociobiology 68 , e5443 (2021). Y. Huang, Q. Shi, A survey of the genes encoding trehalose-metabolism enzymes in crustaceans. J. Crustacean. Biol. 43 (2023). S. G. Da Costa-Latgé, P. Bates, R. Dillon, F. A. Genta, Characterization of glycoside hydrolase families 13 and 31 reveals expansion and diversification of α-amylase genes in the phlebotomine Lutzomyia longipalpis and modulation of sandfly glycosidase activities by Leishmania infection. Front. Physiol. 12 , 635633 (2021). A. Inoue, J. Aoki, Phospholipase A 1 : structure, distribution and function. Future Lipidology 1 , 687–700 (2006). T. Hopkins, C. Ragsdale, J. Seo, Elevated ambient temperature reduces fat storage through the FoxO-mediated insulin signaling pathway. PLoS One 20 , e0317971 (2025). A. M. King, T. H. MacRae, Insect heat shock proteins during stress and diapause. Annu. Rev. Entomol. 60 , 59–75 (2015). M. Nasir, A. Mohsan, M. Ahmad, S. Saeed, M. A. Aziz, M. Imran, U. A. A. Sheikh, Effect of different temperatures on colony characteristics of Bombus terrestris (Hymenoptera: Apidae). PJZ 51 (2019). L. Zhu, K. Wang, X. Wu, H. Zheng, X. Liao, Association of specific gut microbiota with polyethylene microplastics caused gut dysbiosis and increased susceptibility to opportunistic pathogens in honeybees. Sci. Total Environ. 918 , 170642 (2024). J. N. Hahladakis, C. A. Velis, R. Weber, E. Iacovidou, P. Purnell, An overview of chemical additives present in plastics: migration, release, fate and environmental impact during their use, disposal and recycling. J. Hazard. Mater. 344 , 179–199 (2018). B. J. Troczka, R. A. Homem, R. Reid, K. Beadle, M. Kohler, M. Zaworra, L. M. Field, M. S. Williamson, R. Nauen, C. Bass, T. G. E. Davies, Identification and functional characterisation of a novel N-cyanoamidine neonicotinoid metabolising cytochrome P450, CYP9Q6, from the buff-tailed bumblebee Bombus terrestris . Insect Biochem. Mol. Biol. 111 , 103171 (2019). J. C. Prata, C. J. M. Silva, D. Serpa, A. M. V. M. Soares, C. Gravato, A. L. Patrício Silva, Mechanisms influencing the impact of microplastics on freshwater benthic invertebrates: Uptake dynamics and adverse effects on Chironomus riparius . Sci. Total Environ. 859 , 160426 (2023). Y. Deng, X. Jiang, H. Zhao, S. Yang, J. Gao, Y. Wu, Q. Diao, C. Hou, Microplastic polystyrene ingestion promotes the susceptibility of honeybee to viral infection. Environ. Sci. Technol. 55 , 11680–11692 (2021). L. Cerenius, K. Söderhäll, The prophenoloxidase-activating system in invertebrates. Immunol. Rev. 198 , 116–126 (2004). D. Wang, B. Y. Kim, K. S. Lee, H. J. Yoon, Z. Cui, W. Lu, J. M. Jia, D. H. Kim, H. D. Sohn, B. R. Jin, Molecular characterization of iron binding proteins, transferrin and ferritin heavy chain subunit, from the bumblebee Bombus ignitus . Comp. Biochem. Physiol. B Biochem. Mol. Biol. 152 , 20–27 (2009). W. Ren, Y. Zhang, M. Li, L. Wu, G. Wang, G.-H. Baeg, J. You, Z. Li, X. Lin, Windpipe controls Drosophila intestinal homeostasis by regulating JAK/STAT pathway via promoting receptor endocytosis and lysosomal degradation. PLOS Genetics 11 , e1005180 (2015). J. Danihlík, K. Aronstein, M. Petřivalský, Antimicrobial peptides: a key component of honey bee innate immunity. J. Apic. Res. 54 , 123–136 (2015). C. E. Riddell, S. Sumner, S. Adams, E. B. Mallon, Pathways to immunity: temporal dynamics of the bumblebee ( Bombus terrestris ) immune response against a trypanosomal gut parasite. Insect Mol. Biol. 20 , 529–540 (2011). X. Li, W. Ma, Y. Jiang, Heat stress affects the expression of antimicrobial peptide genes in adult honeybee ( Apis cerana and Apis mellifera ). Int. J. Trop. Insect. Sci. 42 , 2465–2471 (2022). S. Tsuzuki, M. Ochiai, H. Matsumoto, S. Kurata, A. Ohnishi, Y. Hayakawa, Drosophila growth-blocking peptide-like factor mediates acute immune reactions during infectious and non-infectious stress. Sci. Rep. 2 , 210 (2012). W. R. Simmons, D. R. Angelini, Chronic exposure to a neonicotinoid increases expression of antimicrobial peptide genes in the bumblebee Bombus impatiens . Sci. Rep. 7 , 44773 (2017). L. R. Runtuwene, S. Kawashima, V. D. Pijoh, J. S. B. Tuda, K. Hayashida, J. Yamagishi, C. Sugimoto, S. Nishiyama, M. Sasaki, Y. Orba, H. Sawa, T. Takasaki, A. A. James, T. Kobayashi, Y. Eshita, The lethal(2)-essential-for-life L(2)EFL gene family modulates Dengue virus infection in Aedes aegypti . Int. J. Mol. Sci. 21 , 7520 (2020). B. Gagliardi, S. M. Long, V. J. Pettigrove, P. C. Griffin, A. A. Hoffmann, A re-evaluation of chironomid deformities as an environmental stress response: avoiding survivorship bias and testing noncontaminant biological factors. Environ. Toxicol. Chem. 38 , 1658–1667 (2019). J. E. Mendoza, D. Tineo, B. Chuquibala-Checan, N. Atalaya-Marin, V. H. Taboada-Mitma, J. Tafur-Culqui, E. Tarrillo, D. Gómez-Fernández, M. Goñas, M. A. Reyes-Reyes, Global perspectives on the biodegradation of LDPE in agricultural systems. Front. Microbiol. 15 , 1510817 (2025). W. Kämper, P. K. Werner, A. Hilpert, C. Westphal, N. Blüthgen, T. Eltz, S. D. Leonhardt, How landscape, pollen intake and pollen quality affect colony growth in Bombus terrestris . Landsc. Ecol. 31 , 2245–2258 (2016). J. I. Raine, X. Li, L. Newstrom-Lloyd, New Zealand bee pollen catalogue (2022). U. Facchini, M. Milesi, L. Sesana, R. A. Bernasconi, A. Mussoni, Ozone measurements in Northern Italy and in canton Ticino, Switzerland. Trans. Ecol. Environ. 37 , 573–580 (1999). OECD 247, OECD guideline for the testing of chemicals , Bumblebee, acute oral toxicity test (2017). D. Seidenath, A. R. Weig, A. Mittereder, T. Hillenbrand, D. Brüggemann, T. Opel, N. Langhof, M. Riedl, H. Feldhaar, O. Otti, Diesel exhaust particles alter gut microbiome and gene expression in the bumblebee Bombus terrestris . Ecol. Evol. 13 , e10180 (2023). S. Wagner, T. Hüffer, P. Klöckner, M. Wehrhahn, T. Hofmann, T. Reemtsma, Tire wear particles in the aquatic environment - a review on generation, analysis, occurrence, fate and effects. Water Res. 139 , 83–100 (2018). V. Demichev, C. B. Messner, S. I. Vernardis, K. S. Lilley, M. Ralser, DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. Nat. Methods 17 , 41–44 (2020). Perez-Riverol Y, Bandla C, Kundu DJ, Kamatchinathan S, Bai, J., S. Hewapathirana, N. S. John, A. Prakash, M. Walzer, S. Wang, J. A. Vizcaíno, The PRIDE database at 20 years: 2025 update. Nucleic Acids Research 53 , D543–D553 (2025). R Core Team (2024), R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2024). T. Therneau, A package for survival analysis in R (2024). A. Kassambara, Kosinski, M., Biecek, P., survminer: drawing survival curves using ‘ggplot2’ (2024). Y. Benjamini, Y. Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing. J. R. Stat. Soc. Ser. B Stat. Methodol. 57 , 289–300 (1995). J. Fox, S. Weisberg, An R companian to applied regression (2019). A. Kassambara, rstatix: pipe-friendly framework for basic statistic (2025). H. Wickham, ggplot2: elegant graphics for data analysis. Springer-Verlag New York (2016). R Core Team (2025), R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2025). GitHub, GitHub - vdemichev/DiaNN: DIA-NN - a universal automated software suite for DIA proteomics data analysis (19.01.2026) (available at https://github.com/vdemichev/DiaNN). C. Ammar, M. Gruber, G. Csaba, R. Zimmer, MS-EmpiRe utilizes peptide-level noise distributions for ultra-sensitive detection of differentially expressed proteins. Mol. Cell. Proteom. 18 , 1880–1892 (2019). Additional Declarations The authors declare no competing interests. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-9320368\",\"acceptedTermsAndConditions\":true,\"allowDirectSubmit\":true,\"archivedVersions\":[],\"articleType\":\"Research Article\",\"associatedPublications\":[],\"authors\":[{\"id\":617533264,\"identity\":\"fbccdda1-98c5-4c61-a729-358acb036f7d\",\"order_by\":0,\"name\":\"Gwen Kühn\",\"email\":\"data:image/png;base64,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\",\"orcid\":\"https://orcid.org/0009-0009-5240-0886\",\"institution\":\"Animal Population Ecology, Animal Ecology I, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, D-95440 Bayreuth, Germany\",\"correspondingAuthor\":true,\"prefix\":\"\",\"firstName\":\"Gwen\",\"middleName\":\"\",\"lastName\":\"Kühn\",\"suffix\":\"\"},{\"id\":617533265,\"identity\":\"f4b0c4ae-0af8-43ab-b580-0ebf7e471360\",\"order_by\":1,\"name\":\"Marco M. Rupprecht\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gene Center Munich, Laboratory for Functional Genome Analysis (LAFUGA), LMU München, Munich, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Marco\",\"middleName\":\"M.\",\"lastName\":\"Rupprecht\",\"suffix\":\"\"},{\"id\":617533266,\"identity\":\"548bcc00-915a-4b1e-b9b1-7e6b424da282\",\"order_by\":2,\"name\":\"Magdalena M. Mair\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Statistical Ecotoxicology, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, D-95440 Bayreuth, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Magdalena\",\"middleName\":\"M.\",\"lastName\":\"Mair\",\"suffix\":\"\"},{\"id\":617533267,\"identity\":\"38279d98-970f-4f85-879b-53c45156009c\",\"order_by\":3,\"name\":\"Jan B. Stöckl\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gene Center Munich, Laboratory for Functional Genome Analysis (LAFUGA), LMU München, Munich, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Jan\",\"middleName\":\"B.\",\"lastName\":\"Stöckl\",\"suffix\":\"\"},{\"id\":617533268,\"identity\":\"87fb5717-d1d1-41bd-96a8-d37a01f05e8f\",\"order_by\":4,\"name\":\"Fabienne Kröger\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Animal Population Ecology, Animal Ecology I, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, D-95440 Bayreuth, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Fabienne\",\"middleName\":\"\",\"lastName\":\"Kröger\",\"suffix\":\"\"},{\"id\":617533269,\"identity\":\"24b2c019-c0b1-46ee-a49b-47387e5aa604\",\"order_by\":5,\"name\":\"Alina Schieder\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Animal Population Ecology, Animal Ecology I, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, D-95440 Bayreuth, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Alina\",\"middleName\":\"\",\"lastName\":\"Schieder\",\"suffix\":\"\"},{\"id\":617533270,\"identity\":\"64047ddf-2029-4705-a5c0-a2159b9ade1d\",\"order_by\":6,\"name\":\"Anke Nölscher\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Institute of Climate and Energy Systems – Troposphere (ICE-3), Forschungszentrum Jülich, and Institute of Geophysics and Meteorology, University of Cologne, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Anke\",\"middleName\":\"\",\"lastName\":\"Nölscher\",\"suffix\":\"\"},{\"id\":617533271,\"identity\":\"f3256946-df2e-41ba-a076-b2dec0dbedf1\",\"order_by\":7,\"name\":\"Thomas Fröhlich\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Gene Center Munich, Laboratory for Functional Genome Analysis (LAFUGA), LMU München, Munich, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Thomas\",\"middleName\":\"\",\"lastName\":\"Fröhlich\",\"suffix\":\"\"},{\"id\":617533272,\"identity\":\"4e1491d0-3d9d-4aae-8d00-33e711f31530\",\"order_by\":8,\"name\":\"Heike Feldhaar\",\"email\":\"\",\"orcid\":\"\",\"institution\":\"Animal Population Ecology, Animal Ecology I, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, D-95440 Bayreuth, Germany\",\"correspondingAuthor\":false,\"prefix\":\"\",\"firstName\":\"Heike\",\"middleName\":\"\",\"lastName\":\"Feldhaar\",\"suffix\":\"\"}],\"badges\":[],\"createdAt\":\"2026-04-04 12:16:43\",\"currentVersionCode\":1,\"declarations\":{\"humanSubjects\":false,\"vertebrateSubjects\":false,\"conflictsOfInterestStatement\":false,\"humanSubjectEthicalGuidelines\":false,\"humanSubjectConsent\":false,\"humanSubjectClinicalTrial\":false,\"humanSubjectCaseReport\":false,\"vertebrateSubjectEthicalGuidelines\":false},\"doi\":\"10.21203/rs.3.rs-9320368/v1\",\"doiUrl\":\"https://doi.org/10.21203/rs.3.rs-9320368/v1\",\"draftVersion\":[],\"editorialEvents\":[],\"editorialNote\":\"\",\"failedWorkflow\":false,\"files\":[{\"id\":106300631,\"identity\":\"e0384ca3-b9ef-41dd-96d4-f67d9c77e2b1\",\"added_by\":\"auto\",\"created_at\":\"2026-04-07 09:14:27\",\"extension\":\"png\",\"order_by\":1,\"title\":\"Figure 1\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":57100,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eEffect of the 10-day multiple-stressor (ozone, heat, microplastic) exposure on the survival probability of the bumblebees.\\u003c/strong\\u003e 48 replicates were used per treatment. C = control, O\\u003csub\\u003e3\\u003c/sub\\u003e = ozone, H = heat, HO\\u003csub\\u003e3\\u003c/sub\\u003e = heat + ozone, MP = microplastic, MPO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + ozone, MPH = microplastic + heat, MPHO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + heat + ozone.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage1.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9320368/v1/77b4c0fef1c7bc561099a0dd.png\"},{\"id\":106403650,\"identity\":\"5597c3e5-989c-4500-9114-869087600a2c\",\"added_by\":\"auto\",\"created_at\":\"2026-04-08 09:14:41\",\"extension\":\"png\",\"order_by\":2,\"title\":\"Figure 2\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":362496,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eVolcano plots displaying differentially abundant proteins in the bumblebee fat body proteome in comparison to untreated controls for exposition to (A) ozone (O\\u003c/strong\\u003e\\u003csub\\u003e\\u003cstrong\\u003e3\\u003c/strong\\u003e\\u003c/sub\\u003e\\u003cstrong\\u003e), (B) heat (H), (C) microplastics (MP), (D) heat and ozone (HO\\u003c/strong\\u003e\\u003csub\\u003e\\u003cstrong\\u003e3\\u003c/strong\\u003e\\u003c/sub\\u003e\\u003cstrong\\u003e), (E) MP and ozone (MPO\\u003c/strong\\u003e\\u003csub\\u003e\\u003cstrong\\u003e3\\u003c/strong\\u003e\\u003c/sub\\u003e\\u003cstrong\\u003e), (F) MP and heat (MPH), (G) MP, heat, and ozone (MPHO\\u003c/strong\\u003e\\u003csub\\u003e\\u003cstrong\\u003e3\\u003c/strong\\u003e\\u003c/sub\\u003e\\u003cstrong\\u003e).\\u003c/strong\\u003e Proteins less abundant than in controls are marked in blue, while more abundant proteins are marked in red. Proteins marked in grey are not significantly altered in abundance (t-test q-value \\u0026lt; 0.05; log\\u003csub\\u003e2 \\u003c/sub\\u003efold change \\u0026gt; |1.5|).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage2.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9320368/v1/099c2c6f1d363aa45ff3eeca.png\"},{\"id\":106300634,\"identity\":\"f993cc12-ac80-440a-a5c9-6896360ebd21\",\"added_by\":\"auto\",\"created_at\":\"2026-04-07 09:14:27\",\"extension\":\"png\",\"order_by\":3,\"title\":\"Figure 3\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":505649,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eBubble plot showing log₂ fold changes of proteins (selected following the criteria given in the methods section) with significantly altered abundances in response to exposition to ozone (O\\u003c/strong\\u003e\\u003csub\\u003e\\u003cstrong\\u003e3\\u003c/strong\\u003e\\u003c/sub\\u003e\\u003cstrong\\u003e), heat (H), and microplastic (MP) individually and combined, compared to untreated controls.\\u003c/strong\\u003e Bubble colour indicates the direction of change in protein abundance, while bubble size reflects statistical significance (p-values adjusted for multiple testing). Shaded areas referring to the brackets on the right-hand edge indicate the biological context of the respective proteins.\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage3.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9320368/v1/9947ab4a67700ea4fbdfa00f.png\"},{\"id\":106300635,\"identity\":\"d7f46896-eae3-416a-a08d-267dbbbb43aa\",\"added_by\":\"auto\",\"created_at\":\"2026-04-07 09:14:27\",\"extension\":\"png\",\"order_by\":4,\"title\":\"Figure 4\",\"display\":\"\",\"copyAsset\":false,\"role\":\"figure\",\"size\":175904,\"visible\":true,\"origin\":\"\",\"legend\":\"\\u003cp\\u003e\\u003cstrong\\u003eEffect of the 10-day multiple-stressor (ozone, heat, microplastic) exposure on the relative fat body content of surviving bumblebees.\\u003c/strong\\u003e Red dots and displayed numbers represent the means. Different letters indicate statistically significant differences between treatments. C = control (n = 23 surviving bumblebees), O\\u003csub\\u003e3\\u003c/sub\\u003e = ozone (n = 23), H = heat (n = 22), MP = microplastic (n = 17), HO\\u003csub\\u003e3\\u003c/sub\\u003e = heat + ozone (n = 22), MPO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + ozone (n = 15), MPH = microplastic + heat (n = 12), MPHO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + heat + ozone (n = 10).\\u003c/p\\u003e\",\"description\":\"\",\"filename\":\"floatimage4.png\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9320368/v1/9e456c8f157c26c893c59a82.png\"},{\"id\":106405647,\"identity\":\"85bd7157-ba5d-4ea1-bda0-b6517945f938\",\"added_by\":\"auto\",\"created_at\":\"2026-04-08 09:28:02\",\"extension\":\"pdf\",\"order_by\":0,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"manuscript-pdf\",\"size\":2560842,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"manuscript.pdf\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9320368/v1/c69ab1bf-5f14-4da2-96e2-0eb871fd74c0.pdf\"},{\"id\":106300632,\"identity\":\"51bde14b-32f8-4e33-a78a-0f3a330e1c10\",\"added_by\":\"auto\",\"created_at\":\"2026-04-07 09:14:27\",\"extension\":\"docx\",\"order_by\":1,\"title\":\"\",\"display\":\"\",\"copyAsset\":false,\"role\":\"supplement\",\"size\":376716,\"visible\":true,\"origin\":\"\",\"legend\":\"\",\"description\":\"\",\"filename\":\"Supplementarymaterial.docx\",\"url\":\"https://assets-eu.researchsquare.com/files/rs-9320368/v1/accd31d9d0fbbc166c4c9138.docx\"}],\"financialInterests\":\"The authors declare no competing interests.\",\"formattedTitle\":\"\\u003cp\\u003e\\u003cstrong\\u003eNegative effects of increased ozone concentrations and heat stress on bumblebees are exacerbated by microplastics\\u003c/strong\\u003e\\u003c/p\\u003e\",\"fulltext\":[{\"header\":\"Teaser\",\"content\":\"\\u003cp\\u003eOzone and heat only increase bumblebee mortality combined with microplastics, but then the magnitude exceeds expectations.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\"},{\"header\":\"Introduction\",\"content\":\"\\u003cp\\u003eInsect pollinators support the majority of the world\\u0026rsquo;s plant diversity and the organisms that are associated with it (\\u003cem\\u003e1\\u003c/em\\u003e). About 20 percent of the plants that benefit from insect pollination depend on bee pollination (\\u003cem\\u003e1\\u003c/em\\u003e). Among wild bees, bumblebees are of particular ecological importance, as many bumblebees are generalist pollinators essential for a large number of plant species (e.g. \\u003cem\\u003e2\\u003c/em\\u003e). However, in Europe for instance, 21 percent of the 63 bumblebee species assessed by the International Union for Conservation of Nature (IUCN) are classified as threatened (\\u003cem\\u003e3\\u003c/em\\u003e). Currently, stressors resulting from anthropogenic environmental changes pose severe threats to global biodiversity and associated ecosystem functioning (e.g. \\u003cem\\u003e4\\u003c/em\\u003e). The most important stressors endangering bumblebee health include habitat loss, fragmentation, degradation and associated challenges, as well as climate change, pathogens, pesticides, and further anthropogenic pollutants (e.g. \\u003cem\\u003e3\\u003c/em\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eIn their natural environment, bumblebees are not exposed to isolated single stressors but instead are confronted with combinations of several stressors at the same time (\\u003cem\\u003e5\\u003c/em\\u003e). On top of that, multiple stressors can interact in complex ways, causing effects that deviate from expected combined effects (\\u003cem\\u003e3\\u003c/em\\u003e). Generally, multiple stressors can lead to three types of effects in organisms: First, effects can be as expected, where the combined effect reflects the joint influence of individual stressor effects (see Sch\\u0026auml;fer \\u0026amp; Piggott for different methods for effect combination, \\u003cem\\u003e6\\u003c/em\\u003e). Expected combined effects have been observed in honey bees (\\u003cem\\u003eApis mellifera\\u003c/em\\u003e), where the exposure to three different metals, arsenic, lead, and copper slowed down appetitive learning and reduced long-term memory specificity (\\u003cem\\u003e7\\u003c/em\\u003e). Second, antagonistic effects can occur, where the combined effect of stressors is lower than expected based on the observation of the individual stressor effects. For instance, effects on hypopharyngeal gland size (\\u003cem\\u003e8\\u003c/em\\u003e) in honeybees exposed to both, \\u003cem\\u003eVarroa destructor\\u003c/em\\u003e mites and neonicotinoids effects were weaker as compared to honeybees exposed to only one of those stressors. And third, synergistic effects may be observed, where the combined effect is higher than expected based on the observation of the effects of the individual stressors. For instance, the simultaneous exposure to different pesticides, such as insecticide-fungicide mixtures at sublethal concentrations was shown to synergistically increase mortality in the honeybee, the bumblebee \\u003cem\\u003eBombus terrestris\\u003c/em\\u003e, and the solitary mason bee \\u003cem\\u003eOsmia bicornis\\u003c/em\\u003e (\\u003cem\\u003e9\\u003c/em\\u003e). It is assumed that the ergosterol-biosynthesis inhibiting fungicides inhibit a detoxification pathway that would also be needed to detoxify the insecticide (\\u003cem\\u003e10\\u003c/em\\u003e), resulting in amplified negative effects when bees are confronted with both pesticides together.\\u003c/p\\u003e\\n\\u003cp\\u003eAs synergistic effects of multiple stressors pose the greatest risk to bumblebee health and likely contribute to their decline, it is vital to compare other stressor combinations and gain an understanding of the underlying biochemical mechanisms that mediate negative effects. Currently, knowledge about the effects of stressor combinations other than those including pesticides is scarce.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eBumblebees could be particularly sensitive to increased tropospheric ozone concentrations due to their high respiratory activity during flight (\\u003cem\\u003e11\\u003c/em\\u003e). Tropospheric (near-surface) ozone is a secondary pollutant, as it is not directly produced and emitted but formed in the air. Anthropogenic pollution contains nitrogen oxides (NO\\u003csub\\u003ex\\u003c/sub\\u003e; e.g. \\u003cem\\u003e12\\u003c/em\\u003e) which are for instance generated by combustion vehicles or during energy production from fossil fuels. Together with other gaseous airborne compounds (methane, hydrocarbons, carbon monoxide) the non-linear photochemistry of NO\\u003csub\\u003ex\\u003c/sub\\u003e yields ozone. Tropospheric ozone concentrations increase with the intensity of solar radiation and temperature (\\u003cem\\u003e13\\u003c/em\\u003e). Climate change scenarios predict that ozone levels that are classified as harmful to human health will become increasingly common (\\u003cem\\u003e14\\u003c/em\\u003e). Ozone is a highly reactive oxidant gas that can generate reactive oxygen species (ROS; \\u003cem\\u003e15\\u003c/em\\u003e) which could also harm insects. So far, in bees, ozone exposure (80 ppb \\u0026ndash; 200 ppb) was found to affect olfactory recall and detection, which is assumed to result from altered antennal activity (\\u003cem\\u003e16\\u003c/em\\u003e). In honeybees, exposure to 80 ppb for one hour decreased the activity rate of the antioxidative enzyme superoxide dismutase (\\u003cem\\u003e16\\u003c/em\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eAnother stressor that is steadily increasing in intensity is heat. For the year 2024, the annually averaged global mean near-surface temperature was 1.55 \\u0026deg;C \\u0026plusmn; 0.13 \\u0026deg;C above the 1850\\u0026ndash;1900 average (\\u003cem\\u003e17\\u003c/em\\u003e), and the frequency and intensity of heat waves are also increasing (\\u003cem\\u003e18\\u003c/em\\u003e). Acute heat stress can have various negative effects on insects, including increased mortality and decreased fertility (e.g. \\u003cem\\u003e19\\u003c/em\\u003e). While global warming is predicted to advance further, bumblebees could be particularly affected as they are generally considered cold-adapted (\\u003cem\\u003e20\\u003c/em\\u003e). Hot temperatures are already contributing to declines of more cold-adapted bumblebee species (\\u003cem\\u003e21\\u003c/em\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eOne stressor that has received less attention in multiple-stressor studies to date is microplastic (MP) pollution. MP refers to plastic particles smaller than 1000 \\u0026micro;m (\\u003cem\\u003e22\\u003c/em\\u003e) that are either intentionally added to products (i.e., primary MP) or created by the breakdown of larger plastic debris in the environment (i.e., secondary MP; \\u003cem\\u003e23\\u003c/em\\u003e). The presence of MP in the environment has become a cause of concern in recent decades. Due to increasing global plastic production and improper disposal, the presence of MP particles in the environment is steadily increasing (\\u003cem\\u003e24\\u003c/em\\u003e). As most plastic waste is discarded within terrestrial ecosystems, organisms in these ecosystems might be particularly affected (\\u003cem\\u003e25\\u003c/em\\u003e). Adverse health effects of MP on terrestrial organisms have already been observed in many studies: in terrestrial insects it was shown that MP-polluted food can increase mortality (\\u003cem\\u003e26\\u003c/em\\u003e) and negatively affect growth and body size (\\u003cem\\u003e27\\u003c/em\\u003e). Pollinators like bumblebees can get in contact with MP during foraging in MP polluted areas with contaminated nectar and pollen after atmospheric deposition of MP on flowers (\\u003cem\\u003e28\\u003c/em\\u003e). Additionally, flight activity of bumblebees can further increase MP exposure. Due to friction with air, electrical charges accumulate on the body surface of bees (\\u003cem\\u003e29\\u003c/em\\u003e) which in turn increases the adherence of airborne particulate pollutants (e.g. \\u003cem\\u003e30\\u003c/em\\u003e) such as MP. When transported back into colonies, MP is potentially ingested and distributed among worker bumblebees (e.g. \\u003cem\\u003e31\\u003c/em\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eIn nature, the three stressors increased tropospheric ozone concentrations, heat stress and MP pollution are likely to simultaneously affect bumblebees. The exact effects of these stressors on bumblebee health are not yet fully understood. In order to analyse the effects of the individual stressors and their combination, \\u003cem\\u003eB. terrestris\\u003c/em\\u003e was exposed to each stressor individually as well as in all possible combinations of two and all three stressors together. In addition to assessing mortality, we quantitatively analysed the fat body proteome of \\u003cem\\u003eB. terrestris\\u003c/em\\u003e. The proteomic profiles were compared across all treatment groups to identify biochemical mechanisms underlying the observed health effects. Furthermore, we measured relative fat body content as a proxy for metabolic costs and health status of the surviving bumblebees (\\u003cem\\u003e32\\u003c/em\\u003e).\\u003c/p\\u003e\"},{\"header\":\"Results\",\"content\":\"\\u003cp\\u003e\\u003cem\\u003eBumblebee mortality\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThroughout the 10-day exposure to ozone, heat, and MP as single stressors or in combinations of two or all three stressors, the mortality of bumblebee workers differed significantly between the different treatment groups (Log-Rank test, p = 3 \\u0026middot; 10\\u003csup\\u003e-14\\u003c/sup\\u003e, \\u0026chi;\\u003csup\\u003e2\\u003c/sup\\u003e(df)= 78.4 (7), Fig. 1).\\u003c/p\\u003e\\n\\u003cp\\u003eIn treatment groups without MP (individual stressors: H, O\\u003csub\\u003e3\\u003c/sub\\u003e; combined stressors: HO\\u003csub\\u003e3\\u003c/sub\\u003e), the mortality was not significantly different from the control (see Tab.1 for p values and Tab.S1 for test statistics; Fig. 1). All treatment groups including MP as a stressor, either MP alone, in combination with ozone or heat, or when all three stressors were combined, had a significantly higher mortality than the control and the treatment groups without MP (Tab.1, Tab.S1; Fig. 1). Furthermore, the treatment group with all three stressors combined (MPHO\\u003csub\\u003e3\\u003c/sub\\u003e) had a significantly higher mortality compared to the treatment group with MP as an individual stressor (Tab. 1, Tab.S1; Fig. 1). For the combination of MP and heat and the combination of MP with ozone, the mortality was not significantly higher compared to MP individually (Tab. 1, Tab.S1; Fig. 1).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 1:\\u003c/strong\\u003e \\u003cstrong\\u003eP-values from pairwise comparisons between the treatment groups using Log-Rank tests (degrees of freedom per comparison = 1, for \\u0026chi;\\u003csup\\u003e2\\u003c/sup\\u003e see Tab. S1) to detect significant differences in survival probability of bumblebees exposed to single stressors or combinations (ozone, heat, microplastic) for 10 days.\\u003c/strong\\u003e Significant results (p \\u0026lt; 0.05) are bold. C = control, O\\u003csub\\u003e3\\u003c/sub\\u003e = ozone, H = heat, MP = microplastic, HO\\u003csub\\u003e3\\u003c/sub\\u003e = heat + ozone, MPO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + ozone, MPH = microplastic + heat, MPHO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + heat + ozone.\\u003c/p\\u003e\\n\\u003ctable style=\\\"width: 4.5e+2pt;border: none;\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMP\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e1.0000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e1.0000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e1.0000\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMP\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0061\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0061\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0061\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.4039\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.4039\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.4039\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0238\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0001\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0001\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0001\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.2175\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0005\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2.3\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2.3\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2.3\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.0686\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e8.8\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.6813\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPHO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e1.1\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e1.1\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e1.1\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.0266\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e2.3\\u0026middot;10\\u003csup\\u003e-5\\u003c/sup\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.4063\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.7804\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eChanges in the bumblebee fat body proteome\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eUsing a label-free LC-MS/MS approach, 59.616 peptides were quantified, which could be assigned to 5036 non-redundant proteins, with a false discovery rate (FDR) \\u0026lt; 1% (see Data S2). Among the individual stressors, heat produced the strongest proteomic response with 193 proteins found to be altered in abundance (96 increased and 97 decreased; Fig. 2 B). MP followed with altered abundances of 104 proteins (63 increased and 41 decreased; Fig. 2 C). In comparison, ozone had the least impact altering the abundance of only 31 proteins (16 increased and 15 decreased; Fig. 2 A).\\u003c/p\\u003e\\n\\u003cp\\u003eThe strongest response among the combined stressors was observed for heat combined with ozone, with 296 proteins changed in abundance (173 increased and 123 decreased; Fig. 2 D). The combination of MP with ozone resulted in 200 proteins altered in abundance (117 increased and 83 decreased; Fig. 2 E) exceeding the summed effects of the two individual stressors (O\\u003csub\\u003e3\\u003c/sub\\u003e: 31; MP: 104; see Fig. 2 A \\u0026amp; C). In contrast, the combination of the two stressors that individually induced most changes in protein abundances, heat and MP, altered a total of only 120 proteins (80 increased and 40 decreased; Fig. 2 F). The exposure to all three stressors simultaneously (MP, O₃ and H) did not result in the greatest number of proteins changed in abundance, with 164 proteins altered (90 increased, 74 decreased; Fig. 2 G).\\u003c/p\\u003e\\n\\u003cp\\u003eA variety of proteins associated with immune responses, tissue damage responses, heat responses, responses to toxic substances, oxidative stress responses, and metabolic processes, were differentially abundant in bumblebees after exposition to ozone, heat, and MP individually and combined, in comparison to untreated controls (see Fig. 3; for a full list of all comparisons see Data S3). Among the individual stressors, changes in the abundance of proteins associated with immune responses were most prominent in MP treatment, while changes in the abundance of proteins associated with metabolic processes were most prominent after heat treatment. The ozone treatment was the only single stressor treatment in which the abundance of catalase, a protein directly associated to ROS-responses, was increased in abundance.\\u003c/p\\u003e\\n\\u003cp\\u003eIn multiple stressor treatments, we found that the interaction of several stressors led to proteome changes in areas that were not affected by the corresponding stressors individually (e.g. compare O\\u003csub\\u003e3\\u003c/sub\\u003e, H, and HO\\u003csub\\u003e3\\u003c/sub\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eNotably, proteins linked to immune responses were particularly affected by heat combined with ozone, MP individually and in combination with other stressors, especially MP and ozone, while for heat and ozone individually these effects were less prominent. Furthermore, the abundance of several phospholipase A1 and A2 isoforms showed increased protein abundance for treatments including heat. Strikingly, when all three stressors were present, a significant abundance alteration of the phospholipases was not detected. On the other hand, MP decreased phospholipase abundance, an effect further exacerbated by ozone. In addition, proteins associated with carbohydrate metabolism, including trehalase, alpha-amylase, the glycogen debranching enzyme and several alpha-glucosidase isoforms were less abundant in all treatments except ozone individually. This was particularly pronounced in multiple stressor treatments. Notably, an increase in the abundance of apoptosis-inducing factor 3 was observed exclusively for MP individually and combined with O₃ with and without heat exposures.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eChanges in the bumblebees\\u0026rsquo; relative fat body content\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eEven though differences in the relative fat body content were detected among the treatment groups (Kruskal-Wallis rank sum test, p = 0.03, \\u0026chi;\\u003csup\\u003e2\\u003c/sup\\u003e = 15.31, df = 7), the results were visually not as pronounced as for the mortality (Fig. 4).\\u003c/p\\u003e\\n\\u003cp\\u003eWe only found the relative fat body content to be significantly lower in the treatment group with MP in combination with ozone, both compared to the control and compared to MP alone (Fig. 4, Tab. 2, Tab. S4). \\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eTable 2:\\u003c/strong\\u003e \\u003cstrong\\u003eP-values for the pairwise comparisons between the treatment groups using Log-Rank test (degrees of freedom per comparison = 1, for z-values see Tab. S4) to detect significant differences in relative fat body content of bumblebees exposed to multiple stressors (ozone, heat, microplastic) for 10 days.\\u003c/strong\\u003e Significant results (p \\u0026lt; 0.05) are bold. C = control, O\\u003csub\\u003e3\\u003c/sub\\u003e = ozone, H = heat, MP = microplastic, HO\\u003csub\\u003e3\\u003c/sub\\u003e = heat + ozone, MPO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + ozone, MPH = microplastic + heat, MPHO\\u003csub\\u003e3\\u003c/sub\\u003e = microplastic + heat + ozone.\\u003c/p\\u003e\\n\\u003ctable style=\\\"width: 4.5e+2pt;border: none;\\\"\\u003e\\n \\u003ctbody\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eC\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMP\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.995\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMP\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.995\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eHO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.995\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.995\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.047\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.082\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.082\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003e0.047\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.082\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPH\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.410\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.410\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.406\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003ctr\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e\\u003cstrong\\u003eMPHO\\u003csub\\u003e3\\u003c/sub\\u003e\\u003c/strong\\u003e\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.135\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.284\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.284\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.135\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.284\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.743\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003ctd\\u003e\\n \\u003cp\\u003e0.629\\u003c/p\\u003e\\n \\u003c/td\\u003e\\n \\u003c/tr\\u003e\\n \\u003c/tbody\\u003e\\n\\u003c/table\\u003e\\n\\u003cp\\u003e\\u0026nbsp;\\u003c/p\\u003e\"},{\"header\":\"Discussion\",\"content\":\"\\u003cp\\u003eIn our study, we exposed groups of \\u003cem\\u003eB. terrestris\\u003c/em\\u003e workers to a set of stressors that bumblebees are likely simultaneously exposed to in their natural environment: increased tropospheric ozone concentrations, heat stress, and MP contaminated food. We exposed the bumblebees to these stressors either individually, in combinations of two or all three stressors. MP exposure had the greatest effects on bumblebee health, affecting them significantly at both, the sublethal and lethal level. MP was the only single stressor that increased bumblebee mortality. Furthermore, bumblebee mortality was significantly increased by all stressor combinations including MP. In contrast, ozone and heat individually and their combination did not increase bumblebee mortality, and affected bumblebee health only on the sublethal level. The fat body proteome was differentially altered in all treatments, with different patterns. Additionally, the relative fat body content was significantly lower only in bumblebees treated with the combination of MP and ozone.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eOzone exposure induces oxidative stress response in bumblebees\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eExposure to ozone individually did not influence bumblebee mortality. On the sublethal level however, we found an increased abundance of catalase in the fat body proteome, a change that occurred exclusively in the ozone treatment. Catalase is an important antioxidant enzyme that counteracts ROS-induced oxidative stress and associated damage (e.g. \\u003cem\\u003e33\\u003c/em\\u003e). Ozone is known to be a strong oxidant that directly induces the production of ROS (e.g. \\u003cem\\u003e15\\u003c/em\\u003e). In insects, the exposure to increased ozone concentrations has been shown to result in increased activity of antioxidant enzymes, which are important for neutralizing ROS and preventing damage from oxidative stress (e.g. \\u003cem\\u003e16, 34\\u003c/em\\u003e). Salem et al. (\\u003cem\\u003e34\\u003c/em\\u003e) found catalase activity to increase in the common house mosquito \\u003cem\\u003eCulex pipiens\\u003c/em\\u003e after ozone exposition, supporting our finding. Beyond antioxidant enzymes, we also observed other changes in the fat body proteome that exclusively occurred in the ozone treatment among the single stressor treatments. For example, a protein of the short-chain dehydrogenase/reductase family 16 C, and the phospholipase A2 (A0A9BJS26) was decreased in abundance. These two proteins are important in metabolic processes and signalling (short-chain dehydrogenase/reductase family 16 C\\u0026nbsp;members: \\u003cem\\u003e35\\u003c/em\\u003e; phospholipase A2: \\u003cem\\u003e36\\u003c/em\\u003e). This suggests that ozone exposition may cause a dysregulation of metabolic processes and signalling in bumblebees and negatively affect insect health beyond oxidative damage by ROS. Since there was no significant reduction in the relative fat body content, the effects of increased ozone concentrations on bumblebee health appear to be limited to minor sublethal effects, at least within the exposure period and the concentration of about 120 ppb used in our experiment.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eHeat stress induces changes in bumblebee metabolism\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eSimilar to ozone, heat did not affect bumblebee mortality when applied individually. On the sublethal level, however, heat induced changes in the fat body proteome, including alterations in the abundance of multiple proteins associated with metabolic processes. In insects, heat stress has previously been recorded to induce changes in the metabolism (e.g. \\u003cem\\u003e37\\u003c/em\\u003e). Our proteomic data suggest a switch in the use of energy sources from carbohydrate reserves to lipid reserves under heat stress. While abundances of proteins associated with energy mobilization from carbohydrates were reduced (trehalase: \\u003cem\\u003e38\\u003c/em\\u003e, alpha-1,4 glucan phosphorylase: \\u003cem\\u003e39\\u003c/em\\u003e, glycogen debranching enzyme: \\u003cem\\u003e40\\u003c/em\\u003e) abundances of proteins associated with phospholipid digestion were mostly increased (phospholipase A1 (A0A9B0C041, A0A9B0F3T4, A0A9B0F5E1): \\u003cem\\u003e41\\u003c/em\\u003e). In line with our results, an increased use of lipid reserves under heat stress has been observed in insects before (e.g. in \\u003cem\\u003eDrosophila melanogaster\\u003c/em\\u003e, \\u003cem\\u003e42\\u003c/em\\u003e). However, the putative switch to a more lipid-based energy metabolism was not reflected in a reduction in relative fat body content in this treatment. That said, it should be noted that in our experimental design, the bumblebees had lower energy requirements because their ability and need to move was restricted.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eIn the heat-only treatment, we found no increase in the abundance of heat shock proteins, that are important for maintaining cell homeostasis by protecting substrate proteins from e.g. denaturation due to heat or other stressors (e.g. \\u003cem\\u003e43\\u003c/em\\u003e). However, it must be considered, that the bumblebees were not exposed to short very hot extreme temperatures but to rather mild chronical heat stress. With 33 \\u0026deg;C, the temperature was about 3 \\u0026deg;C above the optimal nest temperature of \\u003cem\\u003eB. terrestris\\u003c/em\\u003e (ranging from 28 \\u0026deg;C to 30 \\u0026deg;C, e.g. \\u003cem\\u003e44\\u003c/em\\u003e), which could have been insufficient to induce heat shock proteins in adult workers.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMP ingestion increases bumblebee mortality\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eMP was the only single stressor that significantly increased bumblebee mortality. This finding is in line with previous studies that observed increased insect mortality after ingestion of MP of various polymer types, sizes, and concentrations (e.g. \\u003cem\\u003e45\\u003c/em\\u003e: \\u003cem\\u003eApis mellifera\\u003c/em\\u003e, PE-spheres, 100 \\u0026micro;m, 10\\u003csup\\u003e5\\u003c/sup\\u003e particles/ml, for 15 d; \\u003cem\\u003e26\\u003c/em\\u003e: \\u003cem\\u003eD. \\u0026nbsp;melanogaster\\u003c/em\\u003e, PS-spheres, 1.8 \\u0026ndash; 2.2 \\u0026micro;m, 0.5 \\u0026micro;g/ml, 14 d, males especially sensitive). Furthermore, the analysis of the fat body proteome revealed that in the MP treatment the abundances of multiple proteins important for immune responses, responses to toxic substances, metabolic processes, tissue damage responses and heat response were altered. These changes were not observed in the ozone- and heat-only treatments. The underlying mechanisms of increased mortality and sublethal adverse health effects after MP ingestion are not fully understood, but are thought to be driven by several factors, including chemical and mechanical or physical effects of the MP particles.\\u003c/p\\u003e\\n\\u003cp\\u003eBesides the polymer itself, plastics usually contain a multitude of toxic substances. Even additive-free plastics, like the LDPE we used, can contain residual monomers, solvents, catalysts from their synthesis or non-intentionally added substances (NIAS) like degradation products and impurities from the manufacturing process (\\u003cem\\u003e46\\u003c/em\\u003e). NIAS are not chemically bound to the polymer matrix and can leach from the plastic (\\u003cem\\u003e46\\u003c/em\\u003e). After ingestion of LDPE‑contaminated food, these leached NIAS may adversely affect bumblebee health. In line with the possible release of toxic substances from the LDPE MP, we found some cytochromes P450, which are important in detoxification processes (e.g. \\u003cem\\u003e47\\u003c/em\\u003e), to be more abundant in the fat body proteome of bumblebees from the MP treatment, but not in the other single stressor treatments. This suggests chemical toxicity to be one of the possible mechanisms explaining the adverse effects on insect health induced by MP.\\u003c/p\\u003e\\n\\u003cp\\u003eIn addition to health effects mediated by toxic chemical substances, the MP particles themselves could mechanically harm insects. For instance, an accumulation of MP particles could result in a blocking of the gut system and entail lower intake of nutrients (e.g. \\u003cem\\u003e48\\u003c/em\\u003e) or induce tissue damage (e.g. \\u003cem\\u003e49\\u003c/em\\u003e). Our fat body proteome results are in line with this assumption. Among the single stressor treatments, we found exclusively for MP increased abundances of some proteins associated with tissue damage responses such as phenoloxidase-activating factor 2 (e.g. \\u003cem\\u003e50\\u003c/em\\u003e), transferrin (e.g. \\u003cem\\u003e51\\u003c/em\\u003e), ferritin light chain and ferritin heavy chain (e.g. \\u003cem\\u003e51\\u003c/em\\u003e), and the protein windpipe as an important regulator of pathways involved in tissue replacement after damage of midgut epithelium (\\u003cem\\u003e52\\u003c/em\\u003e).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eFurthermore, we found (exclusively in the MP-only treatment) increased abundances of two proteins associated with the invertebrate humoral immune response, abaecin and hymenoptaecin (e.g. \\u003cem\\u003e53\\u003c/em\\u003e). These proteins are commonly associated with responses to pathogen challenges (e.g. \\u003cem\\u003e54\\u003c/em\\u003e). However, changes in their abundances in response to non-infectious stress such as heat stress (e.g. \\u003cem\\u003eApis cerana\\u003c/em\\u003e \\u0026amp; \\u003cem\\u003eA. mellifera\\u003c/em\\u003e; \\u003cem\\u003e55\\u003c/em\\u003e), aseptic wounding (e.g. \\u003cem\\u003eD. melanogaster\\u003c/em\\u003e; \\u003cem\\u003e56\\u003c/em\\u003e), or exposure to pesticides (e.g. \\u003cem\\u003eBombus impatiens\\u003c/em\\u003e; \\u003cem\\u003e57\\u003c/em\\u003e) have been observed before. Therefore, it is possible that their abundances could also change after MP ingestion, triggered either by toxic substances, similar to the reaction to pesticides, or by tissue damage caused by the particles themselves. Activated immunity under such abiotic stress is assumed to prevent infection under stressful conditions (\\u003cem\\u003e55\\u003c/em\\u003e).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eOur findings on the fat body proteome support both, chemical and mechanical mechanisms as possible explanations for the adverse health effects after MP ingestion. We suggest further studies to better understand how negative health effects of MP are mediated mechanistically.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eMP exacerbates the negative health effects of ozone and heat\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe found MP to exacerbate the negative health effects of ozone and heat. When applied individually, ozone and heat did not increase bumblebee mortality, but only adversely affected bumblebee health at the sublethal level. However, in combination with MP, bumblebee mortality was increased beyond the effect caused by MP alone. Therefore, the combination with MP appears to amplify the detrimental health effects of ozone and heat to a lethal level\\u0026nbsp;suggesting a synergistic effect. This synergistic effect was strongest for the combination of all three stressors. A conceivable underlying mechanism could be the inhibition of protective responses to one stressor by another. Our results for the fat body proteome support this scenario. We found the abundance of the protein lethal(2) essential for life (A0A9B2JR06), a heat shock(-related) protein (e.g. \\u003cem\\u003e58\\u003c/em\\u003e), to be decreased after MP exposure. Therefore, MP exposure could make bumblebees more susceptible to heat damage, supporting the proposed underlying mechanism.\\u003c/p\\u003e\\n\\u003cp\\u003eFollowing the pattern observed for bumblebee mortality, we would also expect the strongest adverse health effects at the sublethal level in the treatment combining all three stressors. Consequently, we would have anticipated the lowest relative fat body content in this treatment. In contrast however, the relative fat body content was reduced in bumblebees exposed to the treatment combining ozone and MP exclusively. However, the observed pattern was most likely superimposed by a survivorship bias (e.g. \\u003cem\\u003e59\\u003c/em\\u003e), because only individuals that survived the 10-day exposure were included in measurements of sublethal effects. Since mortality rates differed between the treatments, selection for the strongest individuals (the survivors) differed among treatments. Survivors may have had a higher body fat content per se, thereby masking a mutual exacerbation of sublethal effects of combined stressors on the relative fat body content. The higher the mortality rate, the more pronounced this bias is.\\u003c/p\\u003e\\n\\u003cp\\u003eIn conclusion, the exposure of \\u003cem\\u003eB. terrestris\\u003c/em\\u003e workers to the three naturally concurrent stressors, increased ozone concentrations, heat stress, and MP pollution, either alone or in combination, affected bumblebee mortality, fat body proteome and relative fat body content. The single stressors resulted in different proteomic alterations, suggesting different modes of action of the single stressors. While ozone induced changes in the abundance of proteins related to oxidative stress responses, heat stress led to alterations of proteins involved in metabolic processes, and MP induced abundance changes associated with tissue damage responses and detoxification reactions, amongst others. For stressor combinations, especially those including MP, negative health effects were synergistic. We hypothesise that resistance to one stressor (e.g. heat) may be reduced by another stressor (e.g. MP) as an underlying mechanism. Synergistic effects were particularly evident for bumblebee mortality. While mortality was not affected by ozone, heat, and their combination alone, the addition of MP synergistically exacerbated their negative health effects to such an extent, that they resulted in an increased mortality. Our findings suggest, that even if the effects of ozone, heat and MP are not yet serious under current environmental conditions, they may pose a serious health risk in the future, especially under the consideration of the progressive accumulation of MP in the environment, rising temperatures and the resulting increase in ozone levels.\\u003c/p\\u003e\"},{\"header\":\"Materials and Methods\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eExperimental design\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eBumblebee husbandry\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eEight\\u0026nbsp;\\u003cem\\u003eBombus terrestris\\u0026nbsp;\\u003c/em\\u003ecolonies were ordered from Biobest (Westerlo, Belgium). They were kept in their delivery boxes in a climate chamber at constant 26 \\u0026deg;C and 70 % atmospheric moisture under an inverted 12:12 h dark:light cycle. The colonies were fed three times per week with approximately 10 grams of pollen (Imkerpur, Osnabr\\u0026uuml;ck, Germany) and sugar water [1:1 ratio of water to Apiinvert (S\\u0026uuml;dzucker AG, Mannheim, Germany)]\\u0026nbsp;\\u003cem\\u003ead libitum\\u003c/em\\u003e.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eProduction and characterization of microplastic\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe used irregularly shaped low-density polyethylene (LDPE) fragments for the MP-exposure via food. We chose LDPE, since this polymer is one of the most common plastic wastes, and frequently used in agriculture (e.g. as mulching film; see \\u003cem\\u003e60\\u003c/em\\u003e and citations herein). To produce the LDPE fragments, LDPE granules (Lupolen 1800P, Lyondell Basell, Bayreuth, Germany) were milled (centrifugal mill ZM300, RETSCH GmbH, Haan, Germany; rotor: 24Z; sieve: distance sieve 200 \\u0026micro;m) and subsequently sieved with an air jet sieve (e200 LS, Hosokawa Alpine AG, Augsburg, Germany; sieves: 75\\u0026micro;m and 20\\u0026micro;m) to achieve the particle size fraction of 20 \\u0026ndash; 75 \\u0026micro;m we worked with. In this size class, the number particle size distribution showed 50 % of the particles had a diameter (d\\u003csub\\u003e50\\u003c/sub\\u003e) smaller than 25.75 \\u0026mu;m (d\\u003csub\\u003e10\\u003c/sub\\u003e = 15.86 \\u0026mu;m, d\\u003csub\\u003e90\\u003c/sub\\u003e = 55.77 \\u0026mu;m; Fig. S5). We used this size class, as it overlaps extensively with the size of pollen of plants that \\u003cem\\u003eB. terrestris\\u003c/em\\u003e pollinates (\\u003cem\\u003e61, 62\\u003c/em\\u003e). This size overlap guarantees easy ingestion of the MP with food during the experiment. The particle size-distribution was determined by a Microtrac Sync particle analyser (Microtrac RETSCH GmbH, Haan, Germany; Fig. S5).\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eGeneration of ozone\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eFor ozone generation, ambient air was filtered and dehumidified using an air feed pump (Ansyco, analytische Systeme und Componenten GmbH, 76131 Karlsruhe, Germany; see Fig. S6: 1-2), which also created a regulated gas flow of four litres per minute. To regulate the amount of ozone produced, the gas flow was divided into two air streams by a branching with rotary control (see Fig. S6: 3) and one of them was exposed to a UV lamp (LSP035 pen-ray lamp (Hg/Ar), L.O.T.-Oriel GmbH \\u0026amp; Co. KG, 64293 Darmstadt, Germany, see Fig. S6: 4) to generate ozone with the radiation. This ozone-enriched air was subsequently mixed again with the rest of the purified air and led into a 12-litre glass-tank (30 cm x 20 cm x 20 cm; see Fig. S6: 5), that was sealed air-tight with an acrylic glass cover (polymethyl methacrylate, 210 mm x 297 mm x 2 mm) wrapped in a sheet of 50 \\u0026micro;m thick UV-transparent fluorinated ethylene propylene film (200A FEP100, The Chemours Company\\u003csup\\u003eTM\\u003c/sup\\u003e) and body sealant (Teroson\\u0026reg; RB IX, grey, Henkel AG \\u0026amp; Co. KGaA, 40191 D\\u0026uuml;sseldorf, Germany; see Fig. S6: 6). By regulating the amount of air passing the UV lamp via the branching with rotary control, the ozone concentration in the glass tank was controlled. The ozone concentration was constantly tracked using an ozone analyser (Model 49i, range: 0-0.05 \\u0026ndash; 1.0 ppm, Ansyco, analytische Systeme und Componenten GmbH, 76131 Karlsruhe, Germany; see Fig. S6: 8), which extracted air from the glass tank (flow rate: 1.5 L/min) for analysis. We used environmentally relevant ozone concentrations of about 120 ppb (measured values: 127.21 ppb \\u0026plusmn; 4.91 ppb) as they are reached during daily peaks of hot and sunny periods (\\u003cem\\u003e63\\u003c/em\\u003e). Treatments without ozone as a stressor were provided with purified air only, as the UV lamp was turned off.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eMultiple stressor exposition of B. terrestris workers\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eB. terrestris\\u003c/em\\u003e workers were picked randomly from the colonies the day before the experiment. They were individually put into cages (Nicot\\u0026reg;-Queen cage, Nicotplast SAS, Maisod, France) attached to 10-ml syringes (Injekt\\u0026reg; Solo, B Braun Melsungen AG, 34212 Melsungen, Germany) and fed with sugar water from the syringes for acclimatization to the experimental conditions. The workers were randomly divided into eight groups of 48 individuals each, resulting in 384 individuals in total. Care was taken to ensure that each group contained six individuals from each of the eight source colonies. Each group of 48 individuals was assigned to one of the following treatments: control (C), the treatments with individual stressors, microplastic (4.25 % LDPE in the food, MP), heat (33 \\u0026deg;C constantly, H), and ozone (~120 ppb for two hours per day, O\\u003csub\\u003e3\\u003c/sub\\u003e), the treatments with two stressors combined, microplastic and heat (MPH), microplastic and ozone (MPO\\u003csub\\u003e3\\u003c/sub\\u003e), and heat and ozone (HO\\u003csub\\u003e3\\u003c/sub\\u003e), and the treatment with all three stressors combined, microplastic, heat and ozone (MPHO\\u003csub\\u003e3\\u003c/sub\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eThe chronic exposure to the stressors lasted for ten days. Throughout this period, the individuals were provided with water (4 ml) and small portions (0.8 g \\u0026plusmn; 0.1 g) of sucrose-based food dough [based on Apifonda, (S\\u0026uuml;dzucker AG, Mannheim, Germany)] containing the LDPE MP. We calculated the concentration of LDPE added to the food dough (in w/w) to correspond to a concentration of 4.25 % of LDPE (w/V) in sugar water (1:1, Apiinvert:H\\u003csub\\u003e2\\u003c/sub\\u003eO, V/V), the standard food for bumblebees in most experimental set ups with individuals (e.g. \\u003cem\\u003e64, 65\\u003c/em\\u003e). As one kilogram of the food dough contains about twice as much sugar as one litre of the sugar water, we used about twice the amount of LDPE (8.8 %, w/w, for detailed calculation see Tab. S7) to prepare the MP contaminated food dough. With 4.25 %, we selected a MP concentration in a range that has been used previously in studies on MP effects on insects (e.g. \\u003cem\\u003e45\\u003c/em\\u003e for honeybees: up to 10\\u003csup\\u003e5\\u003c/sup\\u003e PE-spheres with a diameter of 100 \\u0026micro;m per ml of honey equals \\u0026asymp; 51 g/L \\u0026asymp; 5 % w/w; calculation in Tab. S8). In the environment such concentrations are currently only found in exceptional situations (e.g. reviewed by \\u003cem\\u003e66\\u003c/em\\u003e: up to 10 % w/w of MP from tire abrasion at roadside sediments). To obtain the right consistency, the food dough was additionally mixed with powdered sugar (15 % by weight in treatments without and 6.2 % by weight in treatments with MP). We chose food dough as sugar source over sugar water, to ensure a constant and uniform provisioning of MP particles with food. In sugar water MP particles could float to the surface due to their lower density and a surfactant would be necessary to suspend the particles. The food dough and water were refreshed every three days to ensure \\u003cem\\u003ead libitum\\u003c/em\\u003e supply. Additionally, to prevent the food dough from drying out and therefore becoming inaccessible as food source, each cage was sprayed daily with 2 ml of deionised water.\\u003c/p\\u003e\\n\\u003cp\\u003eFor exposure to heat or the control temperature, the bumblebees were kept in two identical climate cabinets (Type 3500, Rumed\\u0026reg; Rubarth Apparate GmbH, 30880 Laatzen, Germany) at 60 % to 80 % relative humidity. The temperature was kept constant at 27 \\u0026deg;C for all treatment groups without heat as a stressor, and 33 \\u0026deg;C for all treatment groups with heat as a stressor. Prior to the start of the experiment the temperature for groups with heat as a stressor was increased gradually from 27 \\u0026deg;C to 33 \\u0026deg;C, with a heating rate of 1 \\u0026deg;C per hour to acclimatize the bumblebees to the new temperature. Throughout the experiment the individuals were positioned in the climate cabinets randomly and rotated daily.\\u003c/p\\u003e\\n\\u003cp\\u003eOzone/control exposure was conducted daily for two hours in the fumigated glass tank, which was positioned in an incubator (Stuart\\u0026reg; orbital incubator SI500, Bibby Scientific Limited, Staffordshire, United Kingdom) to keep the experimental temperatures. The required relative humidity was achieved in the glass tank using four pieces of cotton wool balls weighing four grams each (100 % viscose), each soaked in 30 ml of deionised water. Relative humidity and temperature in the glass tank were tracked throughout the exposition using a thermohygrometer (ClimaTemp, Bresser GmbH, 46414 Rhede, Germany). Prior to the two hours of exposure time, the parameters were allowed to stabilize for 30 minutes, during which the animals were already in the closed glass tank. The two-hour exposure time was selected to mimic natural daily peaks in ozone-concentrations. During the gas exposure the bumblebees were stacked within the glass tank in their individual cages. As the individuals differed in distance to the ozone gas inlet, the order of stacking was changed randomly for each exposition.\\u003c/p\\u003e\\n\\u003cp\\u003eAt the end of the experiment, the individuals were evenly (in terms of source colony and number of repetitions) divided into two groups per treatment. One group was assigned to measure the fat body content and one for analysing the proteome of the fat body. All individuals were anesthetized on dry ice. Individuals for fat body analyses were then euthanized on dry ice and subsequently stored frozen at -20 \\u0026deg;C until analysis. For the proteome analysis, the anesthetized individuals were immediately snap frozen with liquid nitrogen and then stored at -80 \\u0026deg;C until analysis.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eProteome analysis\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eProteomic analysis was conducted on fat body tissue of \\u003cem\\u003eB. terrestris\\u003c/em\\u003e. For this analysis, the fat body was dissected from bumblebee bodies within five minutes after thawing frozen specimen for approximately two minutes at room temperature. All collected fat body tissue per individual was transferred to a separate autoclave-sterilised 0.5 ml micro tube, snap-frozen in liquid nitrogen and again stored at -80 \\u0026deg;C upon further analysis. For each treatment group and for the control, the fat body of one individual was randomly selected from each of the eight colonies, resulting in a sample size of n = 8 independent replicates per treatment. Dissected frozen fat bodies were thawed and lysed in 40 \\u0026micro;l lysis buffer (8M Urea, 50 mM ammonium hydrogen carbonate) followed by sonication using a Sonopuls HD3200 cup resonator (BANDELIN electronic GmbH \\u0026amp; Co. KG, Berlin, Germany; 10 seconds pulse, 20 seconds rest, 12 cycles) and then homogenized using QIAshredder (Qiagen, Hilden, Germany) device (20817x g, 1\\u0026thinsp;min). Protein concentrations were determined using the Pierce 660 nm Protein Assay (Thermo Fisher Scientific, Rockford, IL, USA). Proteins were reduced in 4 mM dithiothreitol (DTT) and 1.8 mM tris(2-carboxyethyl)phosphine at 56\\u0026nbsp;\\u0026deg;C for 30 min and then alkylated in 8 mM iodoacetamide at room temperature for 30 min in the dark. The reaction was quenched by adjusting the DTT concentration to 10 mM at RT for 15 min in the dark. After reduction and alkylation, all samples were sequentially digested, first with Lys-C (enzyme-to-protein ratio 1:100, 4 h at 37 \\u0026deg;C, FUJIFILM Wako Chemicals Europe GmbH, Neuss, Germany) followed by trypsin (enzyme-to-protein ratio 1:50, 18 h at 37 \\u0026deg;C, Promega, Madison, WI, USA) after adjusting the urea concentration to 1 M. The digestion was stopped by adding formic acid (FA) to a final concentration of 1%. Peptides were dried in a vacuum concentrator and subsequently reconstituted in 0.1% FA.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eLC-MS/MS analysis was performed on a nanoElute 2-LC system connected to a timsTOF HT mass spectrometer (both Bruker Daltonics Inc., Fremont, CA, USA), operated in the data-independent acquisition (DIA) mode. 750 ng of peptides were first loaded onto a trap column (PepMap Neo trap column (300 \\u0026micro;m\\u0026times; 5 mm, 5 \\u0026micro;m particles, C18, Thermo Fisher Scientific, Waltham, MA, USA)) and separated on a PepSep Ultra C18 25 cm x 75 \\u0026micro;m, 1.5 \\u0026micro;m (Bruker Daltonics Inc., Fremont, CA, USA), at 250 nL/min with a 25 min gradient of 2-25% of solvent B followed by a 12 min increase to 37%. Solvent A consisted of 0.1% FA in water and solvent B of 0.1% FA in acetonitrile. The mass spectrometer was run in the dia-PASEF mode using 21 25 m/z wide windows and ion mobility ramps between 0.85 and 1.27 1/k0. The sample order was randomized, and carryover was minimized by running blanks between samples. Protein identification and peptide quantification was carried out with DIA-NN (v2.2.0; \\u003cem\\u003e67\\u003c/em\\u003e). The \\u003cem\\u003eB. terrestris\\u003c/em\\u003e database (UniProt Reference Proteome UP000835206, retrieval date:28.02.2025) alongside the built-in contaminants fasta file was used. Due to limited annotation in the database, protein selection focused on well-annotated entries. Representative proteins were manually selected based on the following criteria: (i) consistent identification across multiple pairwise comparisons, and (ii) functional relevance to the respective functional groups associated with the applied stressors. The full list of proteins significantly altered in abundance, all differentially altered proteins and a list of all identified proteins can be found in the supplementary material (Data S9, Data S3, and Data S2). The mass spectrometry proteomics data have been deposited to the ProteomeXchange Consortium via the PRIDE (\\u003cem\\u003e68\\u003c/em\\u003e) partner repository with the dataset identifier PXD071780.\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cem\\u003eFat body assays\\u003c/em\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eTo gain insights into the status of energy storage and indications of immune and detoxification reactions (e.g. \\u003cem\\u003e32\\u003c/em\\u003e), we analysed the relative fat body content of treated bumblebees. Therefore, the bumblebee workers (10\\u0026ndash;23 per treatment, depending on how much the number of repetitions was reduced due to mortality) were thawed and their abdomen separated from the rest of the body. The sternites one to five were cut open ventrally. Each abdomen was individually placed into a 5 ml glass vial with snap lid and dried for five days in a drying cabinet at 70 \\u0026deg;C. After drying, the abdomens were weighed using a precision scale (VWR SM1265Di, d = 0.01 mg, VWR International, Leuwen, Belgium) and then covered in 5 ml petroleum ether (boiling range: 40 \\u0026deg;C \\u0026ndash; 60 \\u0026deg;C, containing ~ 2 % n-Hexane, Fisher Scientific, Loughborough, United Kingdom), which was exchanged daily for three days to dissolve the fat body. After this period, the petroleum ether was removed using a glass pipette, and the abdomens were dried again for five days (drying cabinet, 70 \\u0026deg;C). The abdomens were then weighed again. The relative fat body content for each individual was determined as follows:\\u003c/p\\u003e\\n\\u003cp\\u003e(1)\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cimg src=\\\"https://myfiles.space/user_files/58895_8739fc6c57c1c19a/58895_custom_files/img1775552634.png\\\" width=\\\"791\\\" height=\\\"71\\\"\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cbr\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eStatistical analysis\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThe analyses of the mortality (for mortality data see Data S10) and the relative fat body content (for relative fat body content data see Data S11) were conducted in R version 4.4.1 (\\u003cem\\u003e69\\u003c/em\\u003e). To compare the survival between the treatments (48 replicates were used per treatment), we used a Kaplan-Meier estimator (function:\\u0026nbsp;\\u003cem\\u003esurvfit\\u003c/em\\u003e, R package:\\u0026nbsp;\\u003cem\\u003esurvival\\u003c/em\\u003e; \\u003cem\\u003e70\\u003c/em\\u003e). We visualised the survival curves with the function\\u0026nbsp;\\u003cem\\u003eggsurvplot\\u003c/em\\u003e from the\\u0026nbsp;\\u003cem\\u003esurvminer\\u003c/em\\u003e R package (\\u003cem\\u003e71\\u003c/em\\u003e). To analyse the survival data, we applied a Cox-proportional-hazards-model (function:\\u0026nbsp;\\u003cem\\u003ecoxph\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003esurvival\\u003c/em\\u003e; \\u003cem\\u003e70\\u003c/em\\u003e) and used Schoenfeld residuals (function:\\u0026nbsp;\\u003cem\\u003ecox.zph\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003esurvminer\\u003c/em\\u003e; \\u003cem\\u003e71\\u003c/em\\u003e) to test the assumptions of the model. To test for overall differences between the treatments, we applied a Log-Rank test (function:\\u0026nbsp;\\u003cem\\u003esurvdiff\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003esurvival\\u003c/em\\u003e; \\u003cem\\u003e70\\u003c/em\\u003e). Additionally, we conducted pairwise comparisons among treatments, using a Log-Rank test (function:\\u0026nbsp;\\u003cem\\u003epairwise_survdiff\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003esurvminer\\u003c/em\\u003e; \\u003cem\\u003e71\\u003c/em\\u003e). To account for multiple testing, p-values were adjusted following Benjamini \\u0026amp; Hochberg (\\u003cem\\u003e72\\u003c/em\\u003e). For analysing and visualising the results of the fat body assays, we tested our data for deviance from a normal distribution (function:\\u0026nbsp;\\u003cem\\u003eshapiro.test\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003estats\\u003c/em\\u003e; \\u003cem\\u003e69\\u003c/em\\u003e) and homogeneity of variance (function:\\u0026nbsp;\\u003cem\\u003eleveneTest\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003ecar\\u003c/em\\u003e; \\u003cem\\u003e73\\u003c/em\\u003e). Since neither normality nor variance homogeneity assumptions were met, we finally used a Kruskal Wallis rank sum test (function:\\u0026nbsp;\\u003cem\\u003ekruskal.test\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003estats\\u003c/em\\u003e; \\u003cem\\u003e69\\u003c/em\\u003e) to test for overall differences in the relative fat body content among treatments, followed by pairwise comparisons using a Dunns post-hoc-test (function:\\u0026nbsp;\\u003cem\\u003edunn_test\\u003c/em\\u003e, package:\\u003cem\\u003e\\u0026nbsp;rstatix\\u003c/em\\u003e; \\u003cem\\u003e74\\u003c/em\\u003e). Again, p-values were adjusted following Benjamini \\u0026amp; Hochberg (\\u003cem\\u003e72\\u003c/em\\u003e) to correct for multiple testing. To calculate the means of the individual treatments, we used the\\u0026nbsp;\\u003cem\\u003eaggregate\\u003c/em\\u003e function of the\\u0026nbsp;\\u003cem\\u003estats\\u003c/em\\u003e package (\\u003cem\\u003e69\\u003c/em\\u003e). We visualised the data with violin plots (function:\\u0026nbsp;\\u003cem\\u003eggplot\\u003c/em\\u003e, package:\\u0026nbsp;\\u003cem\\u003eggplot2\\u003c/em\\u003e; \\u003cem\\u003e75\\u003c/em\\u003e).\\u003c/p\\u003e\\n\\u003cp\\u003eThe statistical evaluation and bioinformatics of the fat body proteome were performed using R Version 4.5.1 (\\u003cem\\u003e76\\u003c/em\\u003e). The DIA-NN main report was filtered according to recommendations from the developers (\\u003cem\\u003e77\\u003c/em\\u003e). The FDR confidence was set to \\u0026lt; 1%, and proteins were filtered for a minimum of two unique peptides. To identify differentially abundant proteins, MS-EmpiRe (\\u003cem\\u003e78\\u003c/em\\u003e) was used. To account for multiple testing, p-values were adjusted following Benjamini \\u0026amp; Hochberg (\\u003cem\\u003e72\\u003c/em\\u003e; FDR \\u0026lt; 0.05).\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\n \\u003cv:shapetype id=\\\"_x0000_t75\\\" coordsize=\\\"21600,21600\\\" o:spt=\\\"75\\\" o:preferrelative=\\\"t\\\" path=\\\"m@4@5l@4@11@9@11@9@5xe\\\" filled=\\\"f\\\" stroked=\\\"f\\\"\\u003e\\u0026nbsp;\\u003cv:stroke joinstyle=\\\"miter\\\"\\u003e\\u0026nbsp;\\u003cv:formulas\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"if lineDrawn pixelLineWidth 0\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"sum @0 1 0\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"sum 0 0 @1\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"prod @2 1 2\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"prod @3 21600 pixelWidth\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"prod @3 21600 pixelHeight\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"sum @0 0 1\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"prod @6 1 2\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"prod @7 21600 pixelWidth\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"sum @8 21600 0\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"prod @7 21600 pixelHeight\\\"\\u003e\\u0026nbsp;\\u003cv:f eqn=\\\"sum @10 21600 0\\\"\\u003e\\u0026nbsp;\\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:f\\u003e\\n \\u003c/v:formulas\\u003e\\n \\u003cv:path o:extrusionok=\\\"f\\\" gradientshapeok=\\\"t\\\" o:connecttype=\\\"rect\\\"\\u003e\\u0026nbsp;\\u003c/v:path\\u003e\\n \\u003c/v:stroke\\u003e\\n \\u003c/v:shapetype\\u003e\\n \\u003cv:shape id=\\\"_x0000_i1025\\\" type=\\\"#_x0000_t75\\\"\\u003e\\u0026nbsp;\\u003cv:imagedata src=\\\"file:///C%3A/Users/btr8097/AppData/Local/Packages/oice_16_974fa576_32c1d314_255d/AC/Temp/msohtmlclip1/01/clip_image001.png\\\" o:title=\\\"\\\" chromakey=\\\"white\\\"\\u003e\\u0026nbsp;\\u003c/v:imagedata\\u003e\\n \\u003c/v:shape\\u003e\\n\\u003c/p\\u003e\"},{\"header\":\"Declarations\",\"content\":\"\\u003cp\\u003e\\u003cstrong\\u003eAcknowledgments\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eWe kindly acknowledge Daniel Wagner of the subproject Z01 of the CRC 1357 Microplastics for providing and characterizing the used microplastic particles.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eFunding:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) \\u0026ndash; SFB 1357 Mikroplastik \\u0026ndash; Project Number 391977956.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eThis study was supported by the Studienstiftung des deutschen Volkes and the Marianne-Plehn program (MPP), through the PhD and the MPP scholarship of Gwen B\\u0026uuml;chner.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003ePublishing costs of this study were funded by the Open Access Publishing Fund of the University of Bayreuth. Open Access funding enabled and organized by Projekt DEAL.\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eAuthor contributions:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAuthor contributions follow the CRediT model:\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Conceptualization: GK, MMR, AN, TF, HF\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Methodology: GK, MMR, FK, AS, AN, TF, HF\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Investigation: GK, MMR, MMM, JBS, FK, AS, TF\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Visualization: GK, MMR\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp;\\u0026nbsp;Supervision: AN, TF, HF\\u003c/p\\u003e\\n\\u003cp\\u003e\\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; \\u0026nbsp; Writing\\u0026mdash;original draft: GK, MMR, TF, HF\\u003c/p\\u003e\\n\\u003cp\\u003eWriting\\u0026mdash;review \\u0026amp; editing: GK, MMR, MMM, JBS, FK, AS, AN, TF, HF\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eCompeting interests:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAuthors declare that they have no competing interests.\\u003cstrong\\u003e\\u0026nbsp;\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003e\\u003cstrong\\u003eData and materials availability:\\u003c/strong\\u003e\\u003c/p\\u003e\\n\\u003cp\\u003eAll data are available in the main text or the supplementary materials. Data and code for all analyses except proteomics are submitted with this manuscript at first submission. Upon acceptance of the manuscript all data and code will be made publicly available online on Zenodo under: K\\u0026uuml;hn, G. (2026). Negative effects of increased ozone concentrations and heat stress on bumblebees are exacerbated by microplastics [Data set]. Zenodo. https://doi.org/10.5281/zenodo.18429390\\u0026nbsp;\\u003c/p\\u003e\\n\\u003cp\\u003eProteomics data are available via ProteomeXchange with the identifier PXD071780 at \\u003cem\\u003ehttp://www.ebi.ac.uk/pride\\u003c/em\\u003e.\\u003c/p\\u003e\"},{\"header\":\"References\",\"content\":\"\\u003col\\u003e\\n\\u003cli\\u003eJ. Ollerton, Pollinator diversity: distribution, ecological function, and conservation. \\u003cem\\u003eAnnu. Rev. Ecol. Evol. Syst.\\u003c/em\\u003e \\u003cstrong\\u003e48\\u003c/strong\\u003e, 353\\u0026ndash;376 (2017).\\u003c/li\\u003e\\n\\u003cli\\u003eH. H. W. Velthuis, A. van Doorn, A century of advances in bumblebee domestication and the economic and environmental aspects of its commercialization for pollination. \\u003cem\\u003eApidologie\\u003c/em\\u003e \\u003cstrong\\u003e37\\u003c/strong\\u003e, 421\\u0026ndash;451 (2006).\\u003c/li\\u003e\\n\\u003cli\\u003eS. A. Cameron, B. M. Sadd, Global trends in bumble bee health. \\u003cem\\u003eAnnu. Rev. Entomol. \\u003c/em\\u003e\\u003cstrong\\u003e65\\u003c/strong\\u003e, 209\\u0026ndash;232 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eD. L. Wagner, Insect declines in the anthropocene. \\u003cem\\u003eAnnu. Rev. Entomol.\\u003c/em\\u003e \\u003cstrong\\u003e65\\u003c/strong\\u003e, 457\\u0026ndash;480 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eD. Goulson, E. Nicholls, C. Bot\\u0026iacute;as, E. L. Rotheray, Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. \\u003cem\\u003eScience\\u003c/em\\u003e \\u003cstrong\\u003e347\\u003c/strong\\u003e, 1255957 (2015).\\u003c/li\\u003e\\n\\u003cli\\u003eR. B. Sch\\u0026auml;fer, J. J. Piggott, Advancing understanding and prediction in multiple stressor research through a mechanistic basis for null models. \\u003cem\\u003eGlob. Chang. Biol.\\u003c/em\\u003e \\u003cstrong\\u003e24\\u003c/strong\\u003e, 1817\\u0026ndash;1826 (2018).\\u003c/li\\u003e\\n\\u003cli\\u003eC. Monchanin, E. Drujont, J.-M. Devaud, M. Lihoreau, A. B. Barron, Metal pollutants have additive negative effects on honey bee cognition. \\u003cem\\u003eJ. Exp. Biol\\u003c/em\\u003e. \\u003cstrong\\u003e224\\u003c/strong\\u003e (2021).\\u003c/li\\u003e\\n\\u003cli\\u003eS. Bruckner, L. Straub, P. Neumann, G. R. Williams, Negative but antagonistic effects of neonicotinoid insecticides and ectoparasitic mites \\u003cem\\u003eVarroa destructor \\u003c/em\\u003eon \\u003cem\\u003eApis mellifera \\u003c/em\\u003ehoney bee food glands. \\u003cem\\u003eChemosphere\\u003c/em\\u003e \\u003cstrong\\u003e313\\u003c/strong\\u003e, 137535 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eF. Sgolastra, P. Medrzycki, L. Bortolotti, M. T. Renzi, S. Tosi, G. Bogo, D. Teper, C. Porrini, R. Molowny-Horas, J. Bosch, Synergistic mortality between a neonicotinoid insecticide and an ergosterol-biosynthesis-inhibiting fungicide in three bee species. \\u003cem\\u003ePest Manag. Sci. \\u003c/em\\u003e\\u003cstrong\\u003e73\\u003c/strong\\u003e, 1236\\u0026ndash;1243 (2017).\\u003c/li\\u003e\\n\\u003cli\\u003eM. R. Berenbaum, R. M. Johnson, Xenobiotic detoxification pathways in honey bees. \\u003cem\\u003eCurr. Opin. Insect Sci. \\u003c/em\\u003e\\u003cstrong\\u003e10\\u003c/strong\\u003e, 51\\u0026ndash;58 (2015). \\u003c/li\\u003e\\n\\u003cli\\u003eR. K. Suarez, Energy metabolism during insect flight: biochemical design and physiological performance. \\u003cem\\u003ePhysiological and Biochemical Zoology\\u003c/em\\u003e \\u003cstrong\\u003e73\\u003c/strong\\u003e, 765\\u0026ndash;771 (2000).\\u003c/li\\u003e\\n\\u003cli\\u003eI. S. Mudway, F. J. Kelly, Ozone and the lung: a sensitive issue. \\u003cem\\u003eMol. Asp. Med.\\u003c/em\\u003e \\u003cstrong\\u003e21\\u003c/strong\\u003e, 1\\u0026ndash;48 (2000).\\u003c/li\\u003e\\n\\u003cli\\u003eS. Br\\u0026ouml;nnimann, U. Neu, Weekend-weekday differences of near-surface ozone concentrations in Switzerland for different meteorological conditions. \\u003cem\\u003eAtmos. Environ. \\u003c/em\\u003e\\u003cstrong\\u003e31\\u003c/strong\\u003e, 1127\\u0026ndash;1135 (1997).\\u003c/li\\u003e\\n\\u003cli\\u003eE. Hertig, Health-relevant ground-level ozone and temperature events under future climate change using the example of Bavaria Southern Germany. \\u003cem\\u003eAir Qual. Atmos. Health. \\u003c/em\\u003e\\u003cstrong\\u003e13\\u003c/strong\\u003e, 435\\u0026ndash;446 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eV. Bocci, G. Valacchi, F. Corradeschi, C. Aldinucci, S. Silvestri, E. Paccagnini, R. Gerli, Studies on the biological effects of ozone: 7. Generation of reactive oxygen species (ROS) after exposure of human blood to ozone. \\u003cem\\u003eJ. Biol. Regul. Homeost. Agents\\u003c/em\\u003e \\u003cstrong\\u003e12\\u003c/strong\\u003e, 67\\u0026ndash;75 (1998).\\u003c/li\\u003e\\n\\u003cli\\u003eF. D\\u0026eacute;mares, L. Gibert, B. Lapeyre, P. Creusot, D. Renault, M. Proffit, Ozone exposure induces metabolic stress and olfactory memory disturbance in honey bees. \\u003cem\\u003eChemosphere\\u003c/em\\u003e \\u003cstrong\\u003e346\\u003c/strong\\u003e, 140647 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eWMO, \\u003cem\\u003eState of the global climate 2024\\u003c/em\\u003e (World Meteorological Organization, Switzerland, ed. 1368, 2025).\\u003c/li\\u003e\\n\\u003cli\\u003eS. Legg, IPCC, 2021: Climate Change 2021 - the Physical Science basis. \\u003cem\\u003eInteraction\\u003c/em\\u003e \\u003cstrong\\u003e49\\u003c/strong\\u003e, 44\\u0026ndash;45 (2021).\\u003c/li\\u003e\\n\\u003cli\\u003eK. Sales, R. Vasudeva, M. J. G. Gage, Fertility and mortality impacts of thermal stress from experimental heatwaves on different life stages and their recovery in a model insect. \\u003cem\\u003eR. Soc. Open Sci. \\u003c/em\\u003e\\u003cstrong\\u003e8\\u003c/strong\\u003e, 201717 (2021).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. E. Ogilvie, J. R. Forrest, Interactions between bee foraging and floral resource phenology shape bee populations and communities. \\u003cem\\u003eCurr. Opin. Insect Sci. \\u003c/em\\u003e\\u003cstrong\\u003e21\\u003c/strong\\u003e, 75\\u0026ndash;82 (2017).\\u003c/li\\u003e\\n\\u003cli\\u003eP. Soroye, T. Newbold, J. Kerr, Climate change contributes to widespread declines among bumble bees across continents. \\u003cem\\u003eScience\\u003c/em\\u003e \\u003cstrong\\u003e367\\u003c/strong\\u003e, 685\\u0026ndash;688 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eInternational Standard ISO 24187, \\u003cem\\u003ePrinciples for the analysis of microplastics present in the environment\\u003c/em\\u003e (ed. 60, 2023).\\u003c/li\\u003e\\n\\u003cli\\u003eS. Manzoor, N. Naqash, G. Rashid, R. Singh, Plastic material degradation and formation of microplastic in the environment: a review. \\u003cem\\u003eMater. Today Proc. \\u003c/em\\u003e\\u003cstrong\\u003e56\\u003c/strong\\u003e, 3254\\u0026ndash;3260 (2022).\\u003c/li\\u003e\\n\\u003cli\\u003eR. C. Thompson, W. Courtene-Jones, J. Boucher, S. Pahl, K. Raubenheimer, A. A. Koelmans, Twenty years of microplastic pollution research-what have we learned? \\u003cem\\u003eScience\\u003c/em\\u003e \\u003cstrong\\u003e386\\u003c/strong\\u003e, eadl2746 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eA. A. Horton, A. Walton, D. J. Spurgeon, E. Lahive, C. Svendsen, Microplastics in freshwater and terrestrial environments: evaluating the current understanding to identify the knowledge gaps and future research priorities. \\u003cem\\u003eSci Total Environ. \\u003c/em\\u003e\\u003cstrong\\u003e586\\u003c/strong\\u003e, 127\\u0026ndash;141 (2017).\\u003c/li\\u003e\\n\\u003cli\\u003eS. El Kholy, Y. Al Naggar, Exposure to polystyrene microplastic beads causes sex-specific toxic effects in the model insect \\u003cem\\u003eDrosophila melanogaster\\u003c/em\\u003e. \\u003cem\\u003eSci. Rep.\\u003c/em\\u003e \\u003cstrong\\u003e13\\u003c/strong\\u003e, 204 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eS. Shah, M. Ilyas, R. Li, J. Yang, F.-L. Yang, Microplastics and nanoplastics effects on plant-pollinator interaction and pollination biology. \\u003cem\\u003eEnviron. Sci. Technol. \\u003c/em\\u003e\\u003cstrong\\u003e57\\u003c/strong\\u003e, 6415\\u0026ndash;6424 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eD. Sheng, S. Jing, X. He, A.-M. Klein, H.-R. K\\u0026ouml;hler, T. C. Wanger, Plastic pollution in agricultural landscapes: an overlooked threat to pollination, biocontrol and food security. \\u003cem\\u003eNat. Commun.\\u003c/em\\u003e \\u003cstrong\\u003e15\\u003c/strong\\u003e, 8413 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eY. Vaknin, S. Gan-Mor, A. Bechar, B. Ronen, D. Eisikowitch, The role of electrostatic forces in pollination. in \\u003cem\\u003ePollen and Pollination\\u003c/em\\u003e, A. Dafni, M. Hesse, E. Pacini, Eds. (Springer Vienna, Vienna, s.l., 2000), pp. 133\\u0026ndash;142.\\u003c/li\\u003e\\n\\u003cli\\u003eJ.-M. Bonmatin, C. Giorio, V. Girolami, D. Goulson, D. P. Kreutzweiser, C. Krupke, M. Liess, E. Long, M. Marzaro, E. A. D. Mitchell, D. A. Noome, N. Simon-Delso, A. Tapparo, Environmental fate and exposure; neonicotinoids and fipronil. \\u003cem\\u003eEnviron. Sci. Pollut. Res. Int. \\u003c/em\\u003e\\u003cstrong\\u003e22\\u003c/strong\\u003e, 35\\u0026ndash;67 (2015).\\u003c/li\\u003e\\n\\u003cli\\u003eA. M. Alma, G. S. de Groot, M. Buteler, Microplastics incorporated by honeybees from food are transferred to honey, wax and larvae. \\u003cem\\u003eEnviron. Pollut. \\u003c/em\\u003e\\u003cstrong\\u003e320\\u003c/strong\\u003e, 121078 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eE. L. Arrese, J. L. Soulages, Insect fat body: energy, metabolism, and regulation. \\u003cem\\u003eAnnu. Rev. Entomol. \\u003c/em\\u003e\\u003cstrong\\u003e55\\u003c/strong\\u003e, 207\\u0026ndash;225 (2010).\\u003c/li\\u003e\\n\\u003cli\\u003eM. Corona, G. E. Robinson, Genes of the antioxidant system of the honey bee: annotation and phylogeny. \\u003cem\\u003eInsect. Mol. Biol. \\u003c/em\\u003e\\u003cstrong\\u003e15\\u003c/strong\\u003e, 687\\u0026ndash;701 (2006).\\u003c/li\\u003e\\n\\u003cli\\u003eH. H. A. Salem, S. H. Mohammed, R. I. Eltaly, E. M. Elqady, E. El-said, K. H. Metwaly, Effectiveness and biochemical impact of ozone gas and silica nanoparticles on \\u003cem\\u003eCulex pipiens\\u003c/em\\u003e (Diptera: Culicidae). \\u003cem\\u003eSci. Rep.\\u003c/em\\u003e \\u003cstrong\\u003e14\\u003c/strong\\u003e, 19182 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eK. L. Kavanagh, H. J\\u0026ouml;rnvall, B. Persson, U. Oppermann, Medium- and short-chain dehydrogenase/reductase gene and protein families: the SDR superfamily: functional and structural diversity within a family of metabolic and regulatory enzymes. \\u003cem\\u003eExperientia\\u003c/em\\u003e \\u003cstrong\\u003e65\\u003c/strong\\u003e, 3895\\u0026ndash;3906 (2008).\\u003c/li\\u003e\\n\\u003cli\\u003eM. Kilaso, C. Tipgomut, N. Sanguankiattichai, C. Teerapakpinyo, C. Chanchao, Expression and DNA methylation of phospholipase A2 in Thai native honeybees (Hymenoptera: Apidae). \\u003cem\\u003eRuss. J. Dev. Biol.\\u003c/em\\u003e \\u003cstrong\\u003e47\\u003c/strong\\u003e, 190\\u0026ndash;201 (2016).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. F. Gillooly, J. H. Brown, G. B. West, M. van Savage, E. L. Charnov, Effects of size and temperature on metabolic rate. \\u003cem\\u003eScience \\u003c/em\\u003e\\u003cstrong\\u003e293\\u003c/strong\\u003e, 2001, 2248\\u0026ndash;2251 (2001).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. Qin, F. Liu, J. Wu, S. He, M. Imran, W. Lou, H. Li-Byarlay, S. Luo, The molecular characterization and gene expressions of trehalase in bumblebee, \\u003cem\\u003eBombus lantschouensis \\u003c/em\\u003e(Hymenoptera: Apidae). \\u003cem\\u003eSociobiology\\u003c/em\\u003e \\u003cstrong\\u003e68\\u003c/strong\\u003e, e5443 (2021).\\u003c/li\\u003e\\n\\u003cli\\u003eY. Huang, Q. Shi, A survey of the genes encoding trehalose-metabolism enzymes in crustaceans. \\u003cem\\u003eJ. Crustacean. Biol.\\u003c/em\\u003e \\u003cstrong\\u003e43\\u003c/strong\\u003e (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eS. G. Da Costa-Latg\\u0026eacute;, P. Bates, R. Dillon, F. A. Genta, Characterization of glycoside hydrolase families 13 and 31 reveals expansion and diversification of \\u0026alpha;-amylase genes in the phlebotomine \\u003cem\\u003eLutzomyia longipalpis\\u003c/em\\u003e and modulation of sandfly glycosidase activities by \\u003cem\\u003eLeishmania\\u003c/em\\u003e infection. \\u003cem\\u003eFront. Physiol.\\u003c/em\\u003e \\u003cstrong\\u003e12\\u003c/strong\\u003e, 635633 (2021).\\u003c/li\\u003e\\n\\u003cli\\u003eA. Inoue, J. Aoki, Phospholipase A\\u003csub\\u003e1\\u003c/sub\\u003e : structure, distribution and function. \\u003cem\\u003eFuture Lipidology\\u003c/em\\u003e \\u003cstrong\\u003e1\\u003c/strong\\u003e, 687\\u0026ndash;700 (2006).\\u003c/li\\u003e\\n\\u003cli\\u003eT. Hopkins, C. Ragsdale, J. Seo, Elevated ambient temperature reduces fat storage through the FoxO-mediated insulin signaling pathway. \\u003cem\\u003ePLoS One\\u003c/em\\u003e \\u003cstrong\\u003e20\\u003c/strong\\u003e, e0317971 (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eA. M. King, T. H. MacRae, Insect heat shock proteins during stress and diapause. \\u003cem\\u003eAnnu. Rev. Entomol. \\u003c/em\\u003e\\u003cstrong\\u003e60\\u003c/strong\\u003e, 59\\u0026ndash;75 (2015).\\u003c/li\\u003e\\n\\u003cli\\u003eM. Nasir, A. Mohsan, M. Ahmad, S. Saeed, M. A. Aziz, M. Imran, U. A. A. Sheikh, Effect of different temperatures on colony characteristics of \\u003cem\\u003eBombus terrestris \\u003c/em\\u003e(Hymenoptera: Apidae). \\u003cem\\u003ePJZ\\u003c/em\\u003e \\u003cstrong\\u003e51\\u003c/strong\\u003e (2019).\\u003c/li\\u003e\\n\\u003cli\\u003eL. Zhu, K. Wang, X. Wu, H. Zheng, X. Liao, Association of specific gut microbiota with polyethylene microplastics caused gut dysbiosis and increased susceptibility to opportunistic pathogens in honeybees. \\u003cem\\u003eSci. Total Environ.\\u003c/em\\u003e \\u003cstrong\\u003e918\\u003c/strong\\u003e, 170642 (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. N. Hahladakis, C. A. Velis, R. Weber, E. Iacovidou, P. Purnell, An overview of chemical additives present in plastics: migration, release, fate and environmental impact during their use, disposal and recycling. \\u003cem\\u003eJ. Hazard. Mater.\\u003c/em\\u003e \\u003cstrong\\u003e344\\u003c/strong\\u003e, 179\\u0026ndash;199 (2018).\\u003c/li\\u003e\\n\\u003cli\\u003eB. J. Troczka, R. A. Homem, R. Reid, K. Beadle, M. Kohler, M. Zaworra, L. M. Field, M. S. Williamson, R. Nauen, C. Bass, T. G. E. Davies, Identification and functional characterisation of a novel N-cyanoamidine neonicotinoid metabolising cytochrome P450, CYP9Q6, from the buff-tailed bumblebee \\u003cem\\u003eBombus terrestris\\u003c/em\\u003e. \\u003cem\\u003eInsect Biochem. Mol. Biol. \\u003c/em\\u003e\\u003cstrong\\u003e111\\u003c/strong\\u003e, 103171 (2019).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. C. Prata, C. J. M. Silva, D. Serpa, A. M. V. M. Soares, C. Gravato, A. L. Patr\\u0026iacute;cio Silva, Mechanisms influencing the impact of microplastics on freshwater benthic invertebrates: Uptake dynamics and adverse effects on \\u003cem\\u003eChironomus riparius\\u003c/em\\u003e. \\u003cem\\u003eSci. Total Environ. \\u003c/em\\u003e\\u003cstrong\\u003e859\\u003c/strong\\u003e, 160426 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eY. Deng, X. Jiang, H. Zhao, S. Yang, J. Gao, Y. Wu, Q. Diao, C. Hou, Microplastic polystyrene ingestion promotes the susceptibility of honeybee to viral infection. Environ. Sci. Technol. \\u003cstrong\\u003e55\\u003c/strong\\u003e, 11680\\u0026ndash;11692 (2021).\\u003c/li\\u003e\\n\\u003cli\\u003eL. Cerenius, K. S\\u0026ouml;derh\\u0026auml;ll, The prophenoloxidase-activating system in invertebrates. \\u003cem\\u003eImmunol. Rev.\\u003c/em\\u003e \\u003cstrong\\u003e198\\u003c/strong\\u003e, 116\\u0026ndash;126 (2004).\\u003c/li\\u003e\\n\\u003cli\\u003eD. Wang, B. Y. Kim, K. S. Lee, H. J. Yoon, Z. Cui, W. Lu, J. M. Jia, D. H. Kim, H. D. Sohn, B. R. Jin, Molecular characterization of iron binding proteins, transferrin and ferritin heavy chain subunit, from the bumblebee \\u003cem\\u003eBombus ignitus\\u003c/em\\u003e. \\u003cem\\u003eComp. Biochem. Physiol. B Biochem. Mol. Biol.\\u003c/em\\u003e \\u003cstrong\\u003e152\\u003c/strong\\u003e, 20\\u0026ndash;27 (2009).\\u003c/li\\u003e\\n\\u003cli\\u003eW. Ren, Y. Zhang, M. Li, L. Wu, G. Wang, G.-H. Baeg, J. You, Z. Li, X. Lin, Windpipe controls \\u003cem\\u003eDrosophila\\u003c/em\\u003e intestinal homeostasis by regulating JAK/STAT pathway via promoting receptor endocytosis and lysosomal degradation. \\u003cem\\u003ePLOS Genetics\\u003c/em\\u003e \\u003cstrong\\u003e11\\u003c/strong\\u003e, e1005180 (2015).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. Danihl\\u0026iacute;k, K. Aronstein, M. Petřivalsk\\u0026yacute;, Antimicrobial peptides: a key component of honey bee innate immunity. \\u003cem\\u003eJ. Apic. Res. \\u003c/em\\u003e\\u003cstrong\\u003e54\\u003c/strong\\u003e, 123\\u0026ndash;136 (2015).\\u003c/li\\u003e\\n\\u003cli\\u003eC. E. Riddell, S. Sumner, S. Adams, E. B. Mallon, Pathways to immunity: temporal dynamics of the bumblebee (\\u003cem\\u003eBombus terrestris\\u003c/em\\u003e) immune response against a trypanosomal gut parasite. \\u003cem\\u003eInsect Mol. Biol. \\u003c/em\\u003e\\u003cstrong\\u003e20\\u003c/strong\\u003e, 529\\u0026ndash;540 (2011).\\u003c/li\\u003e\\n\\u003cli\\u003eX. Li, W. Ma, Y. Jiang, Heat stress affects the expression of antimicrobial peptide genes in adult honeybee (\\u003cem\\u003eApis cerana \\u003c/em\\u003eand \\u003cem\\u003eApis mellifera\\u003c/em\\u003e). \\u003cem\\u003eInt. J. Trop. Insect. Sci.\\u003c/em\\u003e \\u003cstrong\\u003e42\\u003c/strong\\u003e, 2465\\u0026ndash;2471 (2022).\\u003c/li\\u003e\\n\\u003cli\\u003eS. Tsuzuki, M. Ochiai, H. Matsumoto, S. Kurata, A. Ohnishi, Y. Hayakawa, \\u003cem\\u003eDrosophila\\u003c/em\\u003e growth-blocking peptide-like factor mediates acute immune reactions during infectious and non-infectious stress. \\u003cem\\u003eSci. Rep.\\u003c/em\\u003e \\u003cstrong\\u003e2\\u003c/strong\\u003e, 210 (2012).\\u003c/li\\u003e\\n\\u003cli\\u003eW. R. Simmons, D. R. Angelini, Chronic exposure to a neonicotinoid increases expression of antimicrobial peptide genes in the bumblebee \\u003cem\\u003eBombus impatiens\\u003c/em\\u003e. \\u003cem\\u003eSci. Rep.\\u003c/em\\u003e \\u003cstrong\\u003e7\\u003c/strong\\u003e, 44773 (2017).\\u003c/li\\u003e\\n\\u003cli\\u003eL. R. Runtuwene, S. Kawashima, V. D. Pijoh, J. S. B. Tuda, K. Hayashida, J. Yamagishi, C. Sugimoto, S. Nishiyama, M. Sasaki, Y. Orba, H. Sawa, T. Takasaki, A. A. James, T. Kobayashi, Y. Eshita, The lethal(2)-essential-for-life L(2)EFL gene family modulates Dengue virus infection in \\u003cem\\u003eAedes aegypti\\u003c/em\\u003e. \\u003cem\\u003eInt. J. Mol. Sci. \\u003c/em\\u003e\\u003cstrong\\u003e21\\u003c/strong\\u003e, 7520 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003eB. Gagliardi, S. M. Long, V. J. Pettigrove, P. C. Griffin, A. A. Hoffmann, A re-evaluation of chironomid deformities as an environmental stress response: avoiding survivorship bias and testing noncontaminant biological factors. \\u003cem\\u003eEnviron. Toxicol. Chem.\\u003c/em\\u003e \\u003cstrong\\u003e38\\u003c/strong\\u003e, 1658\\u0026ndash;1667 (2019).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. E. Mendoza, D. Tineo, B. Chuquibala-Checan, N. Atalaya-Marin, V. H. Taboada-Mitma, J. Tafur-Culqui, E. Tarrillo, D. G\\u0026oacute;mez-Fern\\u0026aacute;ndez, M. Go\\u0026ntilde;as, M. A. Reyes-Reyes, Global perspectives on the biodegradation of LDPE in agricultural systems. \\u003cem\\u003eFront. Microbiol. \\u003c/em\\u003e\\u003cstrong\\u003e15\\u003c/strong\\u003e, 1510817 (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eW. K\\u0026auml;mper, P. K. Werner, A. Hilpert, C. Westphal, N. Bl\\u0026uuml;thgen, T. Eltz, S. D. Leonhardt, How landscape, pollen intake and pollen quality affect colony growth in \\u003cem\\u003eBombus terrestris\\u003c/em\\u003e. \\u003cem\\u003eLandsc. Ecol. \\u003c/em\\u003e\\u003cstrong\\u003e31\\u003c/strong\\u003e, 2245\\u0026ndash;2258 (2016).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. I. Raine, X. Li, L. Newstrom-Lloyd, New Zealand bee pollen catalogue (2022).\\u003c/li\\u003e\\n\\u003cli\\u003eU. Facchini, M. Milesi, L. Sesana, R. A. Bernasconi, A. Mussoni, Ozone measurements in Northern Italy and in canton Ticino, Switzerland. \\u003cem\\u003eTrans. Ecol. Environ. \\u003c/em\\u003e\\u003cstrong\\u003e37\\u003c/strong\\u003e, 573\\u0026ndash;580 (1999).\\u003c/li\\u003e\\n\\u003cli\\u003eOECD 247, \\u003cem\\u003eOECD guideline for the testing of chemicals\\u003c/em\\u003e, \\u003cem\\u003eBumblebee, acute oral toxicity test\\u003c/em\\u003e (2017).\\u003c/li\\u003e\\n\\u003cli\\u003eD. Seidenath, A. R. Weig, A. Mittereder, T. Hillenbrand, D. Br\\u0026uuml;ggemann, T. Opel, N. Langhof, M. Riedl, H. Feldhaar, O. Otti, Diesel exhaust particles alter gut microbiome and gene expression in the bumblebee \\u003cem\\u003eBombus terrestris\\u003c/em\\u003e. \\u003cem\\u003eEcol. Evol. \\u003c/em\\u003e\\u003cstrong\\u003e13\\u003c/strong\\u003e, e10180 (2023).\\u003c/li\\u003e\\n\\u003cli\\u003eS. Wagner, T. H\\u0026uuml;ffer, P. Kl\\u0026ouml;ckner, M. Wehrhahn, T. Hofmann, T. Reemtsma, Tire wear particles in the aquatic environment - a review on generation, analysis, occurrence, fate and effects. \\u003cem\\u003eWater Res. \\u003c/em\\u003e\\u003cstrong\\u003e139\\u003c/strong\\u003e, 83\\u0026ndash;100 (2018).\\u003c/li\\u003e\\n\\u003cli\\u003eV. Demichev, C. B. Messner, S. I. Vernardis, K. S. Lilley, M. Ralser, DIA-NN: neural networks and interference correction enable deep proteome coverage in high throughput. \\u003cem\\u003eNat. Methods\\u003c/em\\u003e \\u003cstrong\\u003e17\\u003c/strong\\u003e, 41\\u0026ndash;44 (2020).\\u003c/li\\u003e\\n\\u003cli\\u003ePerez-Riverol Y, Bandla C, Kundu DJ, Kamatchinathan S, Bai, J., S. Hewapathirana, N. S. John, A. Prakash, M. Walzer, S. Wang, J. A. Vizca\\u0026iacute;no, The PRIDE database at 20 years: 2025 update. \\u003cem\\u003eNucleic Acids Research\\u003c/em\\u003e \\u003cstrong\\u003e53\\u003c/strong\\u003e, D543\\u0026ndash;D553 (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eR Core Team (2024), \\u003cem\\u003eR: A language and environment for statistical computing\\u003c/em\\u003e (R Foundation for Statistical Computing, Vienna, Austria, 2024).\\u003c/li\\u003e\\n\\u003cli\\u003eT. Therneau, A package for survival analysis in R (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eA. Kassambara, Kosinski, M., Biecek, P., survminer: drawing survival curves using \\u0026lsquo;ggplot2\\u0026rsquo; (2024).\\u003c/li\\u003e\\n\\u003cli\\u003eY. Benjamini, Y. Hochberg, Controlling the false discovery rate: a practical and powerful approach to multiple testing. \\u003cem\\u003eJ. R. Stat. Soc. Ser. B Stat. Methodol. \\u003c/em\\u003e\\u003cstrong\\u003e57\\u003c/strong\\u003e, 289\\u0026ndash;300 (1995).\\u003c/li\\u003e\\n\\u003cli\\u003eJ. Fox, S. Weisberg, An R companian to applied regression (2019).\\u003c/li\\u003e\\n\\u003cli\\u003eA. Kassambara, rstatix: pipe-friendly framework for basic statistic (2025).\\u003c/li\\u003e\\n\\u003cli\\u003eH. Wickham, ggplot2: elegant graphics for data analysis. \\u003cem\\u003eSpringer-Verlag New York\\u003c/em\\u003e (2016).\\u003c/li\\u003e\\n\\u003cli\\u003eR Core Team (2025), \\u003cem\\u003eR: A language and environment for statistical computing\\u003c/em\\u003e (R Foundation for Statistical Computing, Vienna, Austria, 2025).\\u003c/li\\u003e\\n\\u003cli\\u003eGitHub, \\u003cem\\u003eGitHub - vdemichev/DiaNN: DIA-NN - a universal automated software suite for DIA proteomics data analysis\\u003c/em\\u003e (19.01.2026) (available at https://github.com/vdemichev/DiaNN).\\u003c/li\\u003e\\n\\u003cli\\u003eC. Ammar, M. Gruber, G. Csaba, R. Zimmer, MS-EmpiRe utilizes peptide-level noise distributions for ultra-sensitive detection of differentially expressed proteins. \\u003cem\\u003eMol. Cell. Proteom. \\u003c/em\\u003e\\u003cstrong\\u003e18\\u003c/strong\\u003e, 1880\\u0026ndash;1892 (2019).\\u003c/li\\u003e\\n\\u003c/ol\\u003e\"}],\"fulltextSource\":\"\",\"fullText\":\"\",\"funders\":[{\"identity\":\"74946bc6-beee-4d51-b7f8-79fcbd6c9246\",\"identifier\":\"10.13039/501100001659\",\"name\":\"Deutsche Forschungsgemeinschaft\",\"awardNumber\":\"391977956\",\"order_by\":0},{\"identity\":\"9e182237-ccd7-4d1d-8c90-30a6d05a761a\",\"identifier\":\"10.13039/501100004350\",\"name\":\"Studienstiftung des Deutschen Volkes\",\"awardNumber\":\"Scholarship Gwen Kühn\",\"order_by\":1}],\"hasAdminPriorityOnWorkflow\":false,\"hasManuscriptDocX\":true,\"hasOptedInToPreprint\":true,\"hasPassedJournalQc\":\"\",\"hasAnyPriority\":true,\"hideJournal\":true,\"highlight\":\"\",\"institution\":\"University of Bayreuth\",\"isAcceptedByJournal\":false,\"isAuthorSuppliedPdf\":false,\"isDeskRejected\":\"\",\"isHiddenFromSearch\":false,\"isInQc\":false,\"isInWorkflow\":false,\"isPdf\":false,\"isPdfUpToDate\":true,\"isWithdrawnOrRetracted\":false,\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"Multiple stressors, LDPE, fat body, proteome, synergistic effects\",\"lastPublishedDoi\":\"10.21203/rs.3.rs-9320368/v1\",\"lastPublishedDoiUrl\":\"https://doi.org/10.21203/rs.3.rs-9320368/v1\",\"license\":{\"name\":\"CC BY 4.0\",\"url\":\"https://creativecommons.org/licenses/by/4.0/\"},\"manuscriptAbstract\":\"\\u003cp\\u003eThe intensity of environmental stressors increases due to global change. Under natural conditions, insect pollinators are experiencing multiple stressors simultaneously which may exacerbate the negative effects of individual stressors. Using a fully crossed factorial design, we investigated the effects of ozone, heat, and LDPE microplastics (MP) on \\u003cem\\u003eBombus terrestris\\u003c/em\\u003e health. Changes in the fat body proteome suggest that ozone induces an oxidative stress response, heat induces changes in the metabolism, and MP induces tissue damage responses and detoxification reactions. Among the single stressors, only MP increased bumblebee mortality. However, in combination with MP, also ozone, heat, and both combined increased the mortality. Here the effect strength exceeded expectations, suggesting synergistic effects. We presume a reduced heat resistance in MP-exposed bumblebees as one possible underlying mechanism. Our study suggests that the progressive environmental accumulation of MP, rising temperatures and the associated increase in ozone levels could pose a serious health risk to pollinators in the future.\\u003c/p\\u003e\",\"manuscriptTitle\":\"Negative effects of increased ozone concentrations and heat stress on bumblebees are exacerbated by microplastics\",\"msid\":\"\",\"msnumber\":\"\",\"nonDraftVersions\":[{\"code\":1,\"date\":\"2026-04-07 09:14:23\",\"doi\":\"10.21203/rs.3.rs-9320368/v1\",\"editorialEvents\":[{\"type\":\"communityComments\",\"content\":0}],\"status\":\"published\",\"journal\":{\"display\":true,\"email\":\"info@researchsquare.com\",\"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\":\"fcdcd0db-5f4c-4e60-a89c-4e581b92534f\",\"owner\":[],\"postedDate\":\"April 7th, 2026\",\"published\":true,\"recentEditorialEvents\":[],\"rejectedJournal\":[],\"revision\":\"\",\"amendment\":\"\",\"status\":\"posted\",\"subjectAreas\":[{\"id\":65721805,\"name\":\"Terrestrial Ecology\"},{\"id\":65721806,\"name\":\"Entomology\"}],\"tags\":[],\"updatedAt\":\"2026-04-07T09:14:23+00:00\",\"versionOfRecord\":[],\"versionCreatedAt\":\"2026-04-07 09:14:23\",\"video\":\"\",\"vorDoi\":\"\",\"vorDoiUrl\":\"\",\"workflowStages\":[]},\"version\":\"v1\",\"identity\":\"rs-9320368\",\"journalConfig\":\"researchsquare\"},\"__N_SSP\":true},\"page\":\"/article/[identity]/[[...version]]\",\"query\":{\"redirect\":\"/article/rs-9320368\",\"identity\":\"rs-9320368\",\"version\":[\"v1\"]},\"buildId\":\"XKTyCvWXoU3ODBz1xrDgd\",\"isFallback\":false,\"isExperimentalCompile\":false,\"dynamicIds\":[84888],\"gssp\":true,\"scriptLoader\":[]}","source_license":"CC-BY-4.0","license_restricted":false}