Loss of helpful bacteria within Tribolium castaneum that aid in coping with UVA and UVB stress

Loss of helpful bacteria within Tribolium castaneum that aid in coping with UVA and UVB stress | 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 Loss of helpful bacteria within Tribolium castaneum that aid in coping with UVA and UVB stress Fei-Feng Wang, Min-Er Li, Lu-Lu Dong, Zhao-Kang Liu, Yu-Die Xia, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-5300393/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 Tribolium castaneum (Herbst), which resides in shaded areas avoiding daylight, has developed various adaptation strategies to cope with ultraviolet (UV) stress. In this study, we utilized 16S rRNA amplicon sequencing to assess the diversity of the bacterial communities within T. castaneum following exposure to ultraviolet-A and ultraviolet-B for different durations, and to elucidate the role of microbiome in host response to UV stress. This study revealed that UV irradiation affected the relative abundance of bacterial community within T. castaneum , rather than its species richness. The significant differences were observed in the relative abundance of Proteobacteria and Cyanobacteria, among the comparison of UV irradiation groups at phylum level. Most genes coded by bacteria were annotated on membrane transport, replication and repair, amino acid metabolism, energy metabolism and carbohydrate metabolism with reference to Kyoto Encyclopedia of Genes and Genomes database. However, the significant differences identified in this study were limited, making it challenging to establish a clear relationship between UV irradiation and the bacteria within T. castaneum larvae. Consequently, we propose the viewpoint that the role of bacteria in contributing T. castaneum against UV stress may have been diminished during their development due to the low-UV rearing conditions. Tribolium castaneum Photophobic insect Ultraviolet stress Microbiome 16S rRNA Adaptation strategy Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Organisms employ diverse co-evolutionary mechanisms to mitigate biotic and abiotic stressors. A paradigmatic instance in the realm of insects is the reciprocal evolution between plant defense strategies and phytophagous insects (Santamaria et al. 2018 ; Wang et al. 2023 ). Ultraviolet (UV) light is a significant component of solar radiation and is often considered an abiotic stressor for organisms. Numerous studies have focused on the adverse effects of UV exposure, including DNA damage, lipid peroxidation, cell aging, and developmental disturbance (Hader and Sinha 2005 ; Chuang and Chen 2013 ; Saucedo et al. 2019 ; Kan et al. 2023 ). Insects, in particular, are significantly impacted by UV radiation. Positively, UV acts as a crucial cue for insect navigation, foraging, population dispersal, and courtship (Fukano et al. 2012 ; Schultheiss et al. 2016 ; Peach et al. 2019 ; Ficarrotta et al. 2022 ; Gaudreau et al. 2023 ). Conversely, UV radiation can lead to DNA damage, photooxidative damage, and developmental disturbance. Nevertheless, insects have evolved resistance strategies to mitigate UV-induced impacts, which include alterations in behavior, structure, and physiological processes (Chuang and Chen 2013 ; Potter and Woods 2013 ; Gaudreau et al. 2017 ; Guo et al. 2019 ). Tribolium castaneum (Herbst) (Coleoptera: Tenebrionidae), an important stored grain pest, commonly infests stored grain products and develops within food substrates, avoiding exposure to daylight (Jackowska et al. 2007 ; Chen et al. 2022 ). Stress-responsive genes, such as heat shock protein and cytochrome P450, were significantly up-regulated in T. castaneum during the first 2 hours of ultraviolet-A (UVA) exposure, and genes related to antioxidant, DNA repair, protein folding, carbon flux diversion, and extracellular matrix showed alterations after ultraviolet-B (UVB) exposure (Guo et al. 2019 ; Sang et al. 2012 ). Exposure to UVB resulted in heightened sensitivity in T. castaneum , leading to delayed metamorphosis, extended growth periods, and smaller pupal sizes. Researchers suggest that changes in endocrine signaling represent an adaptive physiological strategy in response to UVB exposure (Sang et al. 2016 ). Furthermore, cuticle properties of T. castaneum larvae exposed to UVA changed, with increased exposure time leading to blurred boundaries of underlying epidermal cells on the dorsal surface, increased secretions deposited up to the epidermal cells, thickening of the exocuticle, and enlargement of the electron-dense outside region of the exocuticle (Liu et al. 2018 ). These studies indicated that T. castaneum , living in low-UV environment, has developed various adaptation strategies in response to acute UV stress. Microbes are integral to ecosystems, exerting a profound influence on complex multicellular organisms and facilitating host adaptation (Waidele et al. 2019 ; Du et al. 2022 ; Deng et al. 2023 ; Sessitsch et al. 2023 ). Certainly, insect microbiomes also play a role in the adaptation of hosts facing environmental disruptions (Soen 2014 ; Shah et al. 2024 ). For instance, the gut microbiome is quite important for insects that feed on woods due to its ability to digest lignocellulose (Auer et al. 2017 ; Schwarz et al. 2023 ). Microbiota such as Wolbachia exhibited potential reproductive manipulation in insects (Joanne et al. 2016 ). Additionally, alterations in bacterial community in invasive leaf miners Liriomyza spp. contributed to host invasion and adaptation (Zhu et al. 2022 ). On account of the benefits of symbiotic bacteria, it interested us how bacteria within T. castaneum aids in coping with UV stress. 16S rRNA amplicon sequencing is a technique commonly used for microbial species identification, involving the selection of variable regions, PCR amplification using universal primers for conservative regions, and subsequent sequencing analysis. This method has been widely used, emerging as a pivotal tool for studying the microbial community composition and structure (Caporaso et al. 2011 ; Christensen et al. 2018 ; Kameoka et al. 2021 ). By using 16S rRNA amplicon sequencing, interactions among insects, microbiome and environments have been analyzed. Factors such as different food sources (Wang et al. 2011 ; Yuan et al. 2021 ), developmental stages (Wang et al. 2011 ; Yun et al. 2014 ), habitats (Yun et al. 2014 ; Nobles and Jackson 2020 ), as well as stressors such as high temperature and pesticides influence the insect microbiome (Sun et al. 2017 ; Zeng et al. 2020 ). Therefore, we attempted to investigate the role of microbiome within T. castaneum in response to UV stress by employing 16S rRNA amplicon sequencing. UV radiation encompasses UVA (315–400 nm), UVB (280–315 nm), and UVC (200–280 nm); UVC is primarily absorbed by the Earth’s atmosphere, leaving UVB (5% − 10%) and UVA (90% − 95%) as the main components reaching the Earth’s surface (Saucedo et al. 2019 ; Sproul 2013). Studies revealed that UV radiation can alter human microbiome, not only in skin (Burns et al. 2019 ), but also in gut (Bosman et al. 2019 ; Rungjang et al. 2022 ). Building on the above knowledge, we investigated the diversity of the bacterial communities within T. castaneum following exposure to UVA and UVB for different durations, and to elucidate the role of the bacteria in insects living in low-UV environments. Materials and methods Insects rearing T. castaneum was reared on an artificial diet (5% yeast supplemented with whole-wheat flour) at 30°C under 60 ± 2% relative humidity in constant darkness. Approximately 200 adults (1–7 days old) laid eggs in flour for one hour, and the eggs were collected and transferred to a new diet after separation with a 60-mesh sieve. The larvae developed to the final instar stage (20-day-old) were used in the study. Treatments with UVA and UVB irradiation The UVA treatment was manipulated by using 365 nm (wavelength peak of emission spectrum) light-emitting diode light (20W, Shenzhen Xinhongxian Photoelectric Technology Co., Ltd., Shenzhen, China). For UVB treatment, it was manipulated by using UV light (UV-B8W29T5, FSL, Foshan, China) emitting spectrum at wavelength peak of 308 nm. Before treatment, the flour on larvae surface was cleaned with sterile water. Larvae subjected to UV treatment received either UVA or UVB irradiation for durations of 20, 40, and 60 min, respectively. The illumination intensity was measured at 300 µW/cm 2 using a UV light meter (TAINA TN-2340, Taiwan, China). Treatment in darkness for 60 min was set as control (CK). Following irradiation or darkness treatments, larvae were continuously reared in darkness. Study on T. castaneum larvae proposed that surface sterilization has minimal impact on microbial load and thus collected samples without dissection nor surface sterilization to obtain the overall microbiome under different treatments (Korša et al. 2022 ). Even so, to eliminate the impacts from flour and microbiota on the surface, the larvae were immersed in 70% ethanol immersion for one minute, and then rinsed twice with sterile water after 24 h of feeding in darkness. Subsequently, larvae were rapidly frozen using liquid nitrogen and stored in a -80℃ refrigerator until DNA extraction. Samples subjected to UVA treatments for different durations were labeled as A20, A40 and A60; while samples subjected to UVB treatments were labeled as B20, B40 and B60, respectively. Each treatment included five biological replicates, with each replicate consisting of 20 individuals. DNA extraction, 16S rRNA amplification, library preparation and sequencing Total genome DNA was extracted using CTAB method. DNA concentration and purity was monitored on 1% agarose gels. According to the concentration, DNA was diluted to 1ng/µL using sterile water. Polymerase chain reaction amplification (PCR) was carried out for V3 to V4 region of the 16S rRNA, with 15 µL of Phusion® High-Fidelity PCR Master Mix (New England Biolabs); 0.2 µM of forward (341F: CCTAYGGGRBGCASCAG) and reverse (806R: GGACTACNNGGGTATCTAAT) primers, and about 10 ng template DNA. Thermal cycling consisted of initial denaturation at 98℃ for 1 min, followed by 30 cycles of denaturation at 98℃ for 10 s, annealing at 50℃ for 30 s, and elongation at 72℃ for 30 s, finally 72℃ for 5 min. Mix same volume of 1× loading buffer (contained SYB green) with PCR products and operate electrophoresis on 2% agarose gel for detection. PCR products was mixed in equidensity ratios. Then, mixture PCR products was purified with Qiagen Gel Extraction Kit (Qiagen, Germany). Sequencing libraries were generated using TruSeq® DNA PCR-Free Sample Preparation Kit (Illumina, USA) following manufacturer's recommendations and index codes were added. The library quality was assessed on the Qubit@ 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2100 system. The library was sequenced on Illumina NovaSeq6000 platform and 250 bp paired-end reads were generated. Bioinformatics and statistical analysis Paired-end reads was assigned to samples based on their unique barcode and truncated by cutting off the barcode and primer sequence. Then, the paired-end reads were merged using FLASH (V1.2.7, http://ccb.jhu.edu/software/FLASH/ ) (Magoč and Salzberg 2011 ), and raw tags were obtained. High-quality clean tags were obtained by quality filtering on the raw tags (Bokulich et al. 2013 ), according to the QIIME (V1.9.1, http://qiime.org/scripts/split_libraries_fastq.html ) quality controlled process (Caporaso et al. 2010 ). The tags were compared with the reference database (Silva database, https://www.arb-silva.de/ ) using UCHIME algorithm (UCHIME Algorithm, http://www.drive5.com/usearch/manual/uchime_algo.html ) to detect chimera sequences (Edgar et al. 2011 ), and then the chimera sequences were removed (Haas et al. 2011 ). Then the effective tags finally obtained. Sequences with ≥ 97% similarity were assigned to the same Operational Taxonomic Units (OTUs), analyzed by Uparse software (Uparse v7.0.1001, http://drive5.com/uparse/ ) (Edgar 2013 ), and representative sequence for each OTU was screened for further annotation. For each representative sequence, the Silva Database ( http://www.arb-silva.de/ ) was used based on Mothur algorithm to annotate taxonomic information (Quast et al. 2013 ). Multiple sequence alignments were conducted using the MUSCLE software (Version 3.8.31, http://www.drive5.com/muscle/ ) to study phylogenetic relationship of different OTUs and the difference of the dominant species in different samples (Edgar 2004 ). OTUs abundance information were normalized using a standard of sequence number corresponding to the sample with the least sequences. Subsequent analysis of alpha diversity and beta diversity were all performed basing on this output normalized data. Alpha diversity is applied in analyzing complexity of species diversity for a sample through 6 indices, including Observed-species, Chao1, Shannon, Good-coverage. All these indices in our samples were calculated with QIIME (Version 1.7.0) and displayed with R software (Version 2.15.3). Beta diversity analysis was used to evaluate differences of samples in species complexity. Beta diversity on weighted Unifrac was calculated by QIIME software (Version 1.9.1). Principal coordinate analysis (PCoA) analysis was displayed by WGCNA package, stat packages and ggplot2 package in R software (Version 2.15.3). Unweighted Pair-group Method with Arithmetic Means (UPGMA) Clustering was performed as a type of hierarchical clustering method to interpret the distance matrix using average linkage and was conducted by QIIME software (Version 1.9.1). Linear discriminant analysis of effect size (LEfSe) ( https://www.omicstudio.cn/tool .) was used to determine OTUs that discriminate among the microbiome with an LDA score greater than 2. Function prediction of microbiome was performed by PICRUSt with reference to Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Langille et al. 2013 ). Results Analysis of 16S rRNA amplicon sequencing In this study, seven sets of data from 35 samples were acquired. A total of 3,588,114 raw paired-end reads were obtained, from which 2,278,846 effective tags were generated (Table S1 ). The average read length ranged from 392 to 425 nt. The effective tags were clustered into 1,928 OTUs, of which 1,564 OTUs (81.12%) could be annotated to the Silva database. Among the annotated OTUs, 81.12% OTUs were annotated at kingdom level, 53.63% at phylum level, 52.59% at class level, 51.24% at order level, 48.13% at family level, 34.96% at genus level, and 11.10% at species level. The OTUs were further categorized into 34 phyla, 80 classes, 166 orders, 260 families, 374 genera, and 210 species. Diversity of bacterial communities within T. castaneum exposed to UVA and UVB The good’s coverage index of all samples, which reflects the sequencing depth truly, exceeded 0.9999 (Table S2). The rarefaction curve trend appeared flat (Fig. 2 a), indicating sequencing data is large enough, and more data will not result in more OTUs. It can reflect the majority of microbial information of samples. This suggested that the sequencing depth has covered all species of the samples basically. The rank abundance reflected the abundance and evenness of OTUs in the samples (Fig. 2 b). The width and smoothness of the curve indicated the abundance and evenness, respectively. Across all larval samples, the quantities of observed species in microbiome were statistically insignificant (Wilcoxon test, P > 0.05) (Fig. 2 c, Table S2). The shannon indices revealed differences in species diversity among the sample groups (Fig. 2 d, Table S2). The diversity of microbiome in the A60 group was higher than in the A20, B20, and CK groups (Wilcoxon test, P < 0.05). Besides, the A40 group showed higher diversity than the A20 group while the B60 group exhibited higher diversity than the A20 and B20 groups ( P < 0.05). PCoA and UPGMA clustering analysis based on weighted Unifrac distance were employed to analyze the diversity of bacterial communities within T. castaneum exposed to UVA and UVB irradiation (Fig. S1 ). The diversity analysis based on weighted Unifrac distance revealed significant difference between group CK and A60 (Wilcoxon test, P < 0.05), as well as between A60 and A40, A60 and B20, respectively (Fig. S1 a). The cluster analysis at phylum level showed that CK and B20, A20 and B40, A40 and B60 formed distinct branches (Fig. S1 c). There was no clear separation observed between CK group and other groups treated by UV irradiation (Fig. S1 ). Comparison of bacterial communities within T. castaneum exposed to UVA and UVB To investigate the exact variation on bacterial communities within T. castaneum exposed to UVA and UVB irradiation, analysis at different levels of the top 10 bacteria was conducted (Fig. 3 ). Proteobacteria and Cyanobacteria were dominant taxa at phylum level, followed with Firmicutes (Fig. 3 a). When exposed to UVA for 20min, T. castaneum exhibited the highest relative abundance of Proteobacteria (74.00 ± 2.00%), significantly higher than in A40, A60 and B60 groups (Student’s t test, P < 0.05), while concurrently displaying a lower abundance of Cyanobacteria (19.23 ± 3.62%) (Fig. S2a). Additionally, the relative abundance of Proteobacteria in B40 group was also higher than in A40 and A60 groups (Fig. S2a). At the genus level, Izhakiella , unidentified Mitochondria , and unidentified Chloroplast were dominant constituents in the bacterial communities (Fig. 3 b). The relative abundance of unidentified Chloroplast was lowest in the A20 group, registering at 19.15 ± 3.60%, significantly lower than relative abundance in A40 (44.20 ± 3.37%), A60 (36.67 ± 6.09%) and B60 (41.07 ± 2.70%) groups (Fig. S2b). The abundance of unidentified Mitochondria remained relatively stable across these samples, ranging from 30.07–40.63%. Apart from the dominant compositions, Pseudomonas occupied a higher proportion in CK group; Enterococcus in A20 and B40; Weissella in A60; Pleionea in A40; and Paracoccus in B20; however, no statistically significant difference was found in relative abundance of these genera among the sample groups (Fig. 3 b). To identify potential biomarkers for each group, LEfSe analysis to simultaneously identify dominant bacteria was conducted. The result showed that Proteobacteria was dominant in A20 group (LDA > 4) (Kruskal-Wallis test, Wilcoxon test, P < 0.05) (Fig. S3). Function prediction of bacteria within T. castaneum exposed to UVA and UVB To further study the function of bacteria in T. castaneum , the abundance of gene encoded by bacteria annotated on KEGG pathway were performed. The KEGG pathway annotation showed that a majority of genes were annotated on Environmental Information Processing, Genetic Information Processing and Metabolism (Fig. 4 a). Within these categories, pathways including membrane transport, replication and repair, amino acid metabolism, energy metabolism and carbohydrate metabolism, exhibited the highest numbers of gene enrichments (Fig. 4 a). The relative abundance annotated on KEGG pathways at level1 and top 10 pathways at level 2 were analyzed among the sample groups. Most pathways displayed no significant difference, except for pathway of metabolism of cofactors and vitamins, and energy metabolism (Fig. 4 b, c). The analysis of other pathways at level2 showed that A20 had a lower relative abundance annotated in metabolic diseases, enzyme families (Fig. S4). Besides, cluster analysis of top 35 enriched KEGG pathways was performed (Fig. S4a). The clustering result differed from UPGMA clustering analysis about diversity of bacterial communities (Fig. S1 c). The CK and B20 groups were clustered together, and A60 showed a relatively close relation; the clustering of B40, B60 and A40 had a similar effect, with A20 as an outgroup (Fig. S4a). Discussion UV radiation has impacted on the evolutionary course of all forms of life, from microorganisms to humans (Rai et al. 2022 ). As previously mentioned, the beetles, T. castaneum have developed various adaptation strategies in response to UV stress (Guo et al. 2019 ; Sang et al. 2012 , 2016 ; Liu et al. 2018 ). Microbiome of insect colonizes on the insect exoskeleton, in the gut and hemocoel, and within insect cells, playing important role in nutrition, protection, and detoxification (Douglas 2015 ). Moreover, it facilitates host adaptation (Joanne et al. 2016 ; Auer et al. 2017 ; Zhu et al. 2022 ; Schwarz et al. 2023 ). To our knowledge, there is a gap in studying the effects of UV irradiation on insect microbiome and the role of microbes in developing adaptation strategies to UV stress for insects. Therefore, we utilized 16S rRNA amplicon sequencing to investigate the diversity of bacterial communities within T. castaneum after exposure to UVA and UVB for different durations, and the role of bacteria within T. castaneum when living in low-UV environment. As results exhibited above, the significant differences observed in this study were limited, there was no clear separation between CK group and other groups treated with UV irradiation. It was challenging to establish a clear relation between UV irradiation and bacteria within T. castaneum larvae. Consequently, we deliberated on the potential influence of UV irradiation on the bacterial communities within T. castaneum larvae. We propose the viewpoint that the bacteria which aids in coping with UVA and UVB stress had been lost in the evolution due to the low-UV habitats; and current bacteria within T. castaneum may have limited functionality in contributing to develop host adaptation strategies to acute UV stress. In this study, while the species richness of samples was statistically insignificant, the relative abundance of bacterial communities varied significantly among the samples. This can be attributed to the fact that only external physical factor was taken in this study, without introducing additional bacterial species such as changes in food source. The dominant bacterial communities observed in samples were Proteobacteria (45.59–74.00%), Cyanobacteria (19.23–44.5%) and Firmicutes (0.45–5.29%) at phylum level. Researches on microbiome within T. castaneum had also highlighted Proteobacteria as a dominant bacterial community, which aligns with our findings. However, varying compositions were reported, with some including Firmicutes and Actinobacteriota (Korša et al.2022; Wang 2020 ). It's worth noting that Korša et al. excluded Cyanobacteria from their study, attributing their presence to the flour (Korša et al.2022), and the low abundance of Cyanobacteria in T. castaneum adult may be attributive to starvation treatment (Wang 2020 ). Similarly, study on Antheraea pernyi showed a significant percentage of Cyanobacteria (85.90% and 93.82%) in the midgut and midgut contents, alongside Firmicutes and Proteobacteria (Zhang et al. 2018 ; Wang et al. 2020 ). But Zhang et al. ( 2018 ) considered the result was caused by the limitations of research methods, suggesting that a large number of chloroplast nucleic acids in the gut of phytophagous Lepidoptera larvae can be amplified by universal primers of bacterial 16S rRNA gene (Zhang et al. 2018 ). In spite of this, the portion and variation of Cyanobacteria and unidentified Chloroplast led to a unneglected problem in this study. Appetite alteration was observed in various organisms, causing a decrease of appetite in juvenile European seabass ( Dicentrarchus labrax ) (Alves et al. 2021 ) and Gilthead Seabream ( Sparus aurata ) (Alves et al. 2020), and an increase in mice and human males (Parikh et al. 2022 , 2023 ). Exposure to high dose of UVB for 120min led to a decrease in the amount of faeces in Galleria mellonella (Sabockyte et al. 2023 )[62]. And the higher levels of viable bacteria observed in UVB-exposed larvae may be due to impaired antimicrobial peptide synthesis, as suggested by Sabockyte et al. ( 2023 ). Furthermore, certain cyanobacteria are known to respond to light. These cyanobacteria produce mycosporine amino acids that absorb UV radiations and confer resistance to several abiotic stresses, they can also transfer genes to plants and animals, providing UV protection (Carletti et al. 2014 ; Rai et al. 2022 ). However, these specific cyanobacteria were not identified in this study. Therefore, while the presence of cyanobacteria in the larvae may be attributed to diet, the variation in cyanobacteria levels could be influenced by remote effects stemming from alterations in appetite or other unknown impacts of UV irradiation. In this study, apart from unidentified Chloroplast (Cyanobacteria), the dominant genera observed were Izhakiella (Enterobacterales), unidentified Mitochondria (Rickettsiales), both belonging to Proteobacteria. The relative abundance of Proteobacteria was higher in A20 and B40 groups compared to A40 and A60 groups, but there was no significant difference in relative abundance of Izhakiella (Enterobacterales) and unidentified Mitochondria (Rickettsiales). These results suggested that UV irradiation had a minor effect on relative abundance of Proteobacteria, but did not significantly affect the two dominant genera within Proteobacteria. This indicated that the alterations observed in Proteobacteria abundance due to UV irradiation were caused by other genera within the microbial community. Beyond that, the dominant genera observed in other studies differed from our findings, which was in larvae and adults of T. castaneum , respectively (Korša et al. 2022 ; Wang 2020 ). This may be attributed to the differences in population sources, sample collection methods and even the rearing conditions of T. castaneum . An important factor to note is the light-dark cycle used in breeding beetles. In our study, the beetles used for experiments were kept in constant darkness, whereas other studies reared beetles under a light-dark cycle of 12:12 or 16:8 (Korša et al. 2022 ; Wang 2020 ). The discrepancy of luminous environments prompts us to analyze the diversity of microbial community in insects living under different light conditions. Among the top 10 most abundance genera, Pseudomonas and Enterococcus were common across our study and the mentioned studies (Korša et al. 2022 ; Wang 2020 ). These genera may play crucial roles in various physiological processes beyond responding to UV stress. Further research is warranted to identify crucial bacteria that respond to UV stress and contribute to host adaptation. Likewise, relative abundance of gene encoded by bacteria and annotated on KEGG pathways at level1 and top 10 pathways at level2 were analyzed between the sample groups. The KEGG pathway annotation revealed that most genes were annotated on membrane transport (Environmental Information Processing), replication and repair (Genetic Information Processing), amino acid metabolism, energy metabolism and carbohydrate metabolism (Metabolism). However, the majority of these pathways showed no significant differences between the groups. Studies demonstrated that nocturnal insects coordinated energy metabolism and antioxidant activity under light stress by lysine succinylation (Huang et al. 2021 ), and larvae of green tree frog ( Litoria caerulea ) exhibited a higher rates of energy expenditure when exposed to high levels of UV radiation compared to those exposed to lower UV levels (Cramp et al. 2022 ). Although differences in energy metabolism were detected in UV irradiation groups, these differences were not observed when compared to control groups. Researches have suggested that stressors such as high temperature and pesticide have effects on insect microbiome (Sun et al. 2017 ; Zeng et al. 2020 ). However, our investigation into the bacteria of T. castaneum subjected to UV irradiation revealed minor effects, with no significant differences observed compared to the CK group. This result leads to the assumption that insects living in low-UV environment may have undergone a loss of crucial bacteria responsible for coping with UV stress over long-term evolution. Additionally, analyzing the microbial community diversity in insects living at various altitudes with different UV intensities may offer new insights. Nevertheless, despite similarities in living conditions, the composition of microbiomes is notably different, even among insects similar to T. castaneum . This underscores the need for further research to compare microbiome differences in insects under various light and UV environments. In studies focused on UV irradiation effects on T. castaneum , demonstrated their ability to develop adaptation strategies, as evidenced by the regulation of stress-responsive gene expression and structural alterations (Guo et al. 2019 ; Sang et al. 2012 , 2016 ; Liu et al. 2018 ). Yet in this study, no bacteria exhibited potential contributions to host adaptation under UV stress. Considering the rearing conditions of T. castaneum , the strong capability to utilize UV or resist UV-induced damage is likely costly. Bacterial symbionts, with their higher mutation rates and susceptibility to gene loss, may inadvertently lose essential genes for their host, potentially leading to replacement by other symbionts (McCutcheon and Moran 2010 ; Coolen et al. 2022). Moreover, structural alterations in T. castaneum exposed to UV irradiation, such as increased secretions deposited up to the epidermal cells and thickened exocuticle, could reduce the likelihood of receiving UV signaling for bacteria within T. castaneum . Thus, the functional role of bacteria in resisting UV stress appears to be costly for both bacteria and T. castaneum . While the assumption of losing crucial bacteria contributing to UV resistance is plausible, further research is essential to unravel the commonalities in microbiome of photophobic insects, and to verify the assumption that photophobic insects adapted to prolonged darkness may abandon microbiota that respond to UV stress. Declarations A uthor contribution Fei-Feng Wang: conceptualization; formal analysis; writing – original draft. Min-Er Li: investigation; formal analysis; data curation. Lu-Lu Dong: investigation; formal analysis. Zhao-Kang Liu: investigation; formal analysis. Yu-Die Xia: investigation. Lin Yu: writing – review and editing. Bao-Li Qiu: supervision; writing – review and editing. Wen Sang: conceptualization; funding acquisition; writing – review and editing. Funding This work was supported by the National Natural Science Foundation of China (31701793), the National Key R & D Program of China (2023YFD1400700), the Natural Science Foundation of Guangdong Province (2023A1515030219), and the Science and Technology Program of Guangzhou (202206010042). D ata availability The data that support the findings of this study are available at NCBI database (Accession No. PRJNA1107833). Ethics approval and consent to participate Not applicable. Consent to participate All authors approved the final version. Consent for publication The manuscript has not been published previously in the same or very similar form in any other journal. The manuscript is not currently under consideration in other journals. Competing interests The authors declare no competing interests. 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(\u003cstrong\u003ea\u003c/strong\u003e) Sample rarefaction curves; (\u003cstrong\u003eb\u003c/strong\u003e) Group rank Abundance; (\u003cstrong\u003ec\u003c/strong\u003e) Box plot of chao1 indices; (\u003cstrong\u003ed\u003c/strong\u003e) Box plot of shannon indices. The asterisks denote statistically significant difference between two groups of samples (\u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05, Wilcoxon test).\u003c/p\u003e","description":"","filename":"2.png","url":"https://assets-eu.researchsquare.com/files/rs-5300393/v1/306b21b384953442177f37d0.png"},{"id":69903596,"identity":"a5d1ebc4-bd33-4e41-88b3-a773f6f8a619","added_by":"auto","created_at":"2024-11-26 12:25:22","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":65031,"visible":true,"origin":"","legend":"\u003cp\u003eThe bacteria of higher relative abundance at phylum/genus level detected by using 16S rRNA amplicon sequencing. (\u003cstrong\u003ea\u003c/strong\u003e) The top 10 bacteria at phylum level; (\u003cstrong\u003eb\u003c/strong\u003e) The top 10 bacteria at genus level.\u003c/p\u003e","description":"","filename":"3.png","url":"https://assets-eu.researchsquare.com/files/rs-5300393/v1/3fd8edda2aa3e3d24d190095.png"},{"id":69902490,"identity":"68eb616b-bd62-426e-bf27-f9b6b7f5b4ec","added_by":"auto","created_at":"2024-11-26 12:17:22","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":66141,"visible":true,"origin":"","legend":"\u003cp\u003eFunction classification by analyzing 16S rRNA amplicon sequencing data in \u003cem\u003eTribolium castaneum\u003c/em\u003e with reference to KEGG database. (\u003cstrong\u003ea\u003c/strong\u003e) Number of gene annotated on KEGG pathway; (\u003cstrong\u003eb\u003c/strong\u003e) Relative abundance of KEGG pathway at level 1; (\u003cstrong\u003ec\u003c/strong\u003e) Relative abundance of top 10 KEGG pathway at level 2. The asterisks denote statistically significant difference between two groups of samples (Student’s t test, \u003cem\u003eP\u003c/em\u003e \u0026lt; 0.05).\u003c/p\u003e","description":"","filename":"4.png","url":"https://assets-eu.researchsquare.com/files/rs-5300393/v1/e3d337f327c8a1f6b88ed7d7.png"},{"id":79870285,"identity":"3b8c9b80-2854-41b8-9229-38a3e202a78a","added_by":"auto","created_at":"2025-04-03 21:10:07","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":960210,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5300393/v1/ba2ad4ce-ebb1-4e2b-9450-ae7be417cb8a.pdf"},{"id":69902491,"identity":"be9f68cf-da6b-43e8-8d1a-bd1814670baa","added_by":"auto","created_at":"2024-11-26 12:17:22","extension":"pdf","order_by":5,"title":"","display":"","copyAsset":false,"role":"supplement","size":1979172,"visible":true,"origin":"","legend":"","description":"","filename":"supplementarymaterials.pdf","url":"https://assets-eu.researchsquare.com/files/rs-5300393/v1/70d5a14621a5f09073e881b1.pdf"}],"financialInterests":"","formattedTitle":"Loss of helpful bacteria within Tribolium castaneum that aid in coping with UVA and UVB stress","fulltext":[{"header":"Introduction","content":"\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eOrganisms employ diverse co-evolutionary mechanisms to mitigate biotic and abiotic stressors. A paradigmatic instance in the realm of insects is the reciprocal evolution between plant defense strategies and phytophagous insects (Santamaria et al. \u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Ultraviolet (UV) light is a significant component of solar radiation and is often considered an abiotic stressor for organisms. Numerous studies have focused on the adverse effects of UV exposure, including DNA damage, lipid peroxidation, cell aging, and developmental disturbance (Hader and Sinha \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e2005\u003c/span\u003e; Chuang and Chen \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Saucedo et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Kan et al. \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Insects, in particular, are significantly impacted by UV radiation. Positively, UV acts as a crucial cue for insect navigation, foraging, population dispersal, and courtship (Fukano et al. \u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e2012\u003c/span\u003e; Schultheiss et al. \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Peach et al. \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Ficarrotta et al. \u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Gaudreau et al. \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Conversely, UV radiation can lead to DNA damage, photooxidative damage, and developmental disturbance. Nevertheless, insects have evolved resistance strategies to mitigate UV-induced impacts, which include alterations in behavior, structure, and physiological processes (Chuang and Chen \u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Potter and Woods \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e2013\u003c/span\u003e; Gaudreau et al. \u003cspan citationid=\"CR23\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Guo et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e). \u003cem\u003eTribolium castaneum\u003c/em\u003e (Herbst) (Coleoptera: Tenebrionidae), an important stored grain pest, commonly infests stored grain products and develops within food substrates, avoiding exposure to daylight (Jackowska et al. \u003cspan citationid=\"CR29\" class=\"CitationRef\"\u003e2007\u003c/span\u003e; Chen et al. \u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Stress-responsive genes, such as heat shock protein and cytochrome P450, were significantly up-regulated in \u003cem\u003eT. castaneum\u003c/em\u003e during the first 2 hours of ultraviolet-A (UVA) exposure, and genes related to antioxidant, DNA repair, protein folding, carbon flux diversion, and extracellular matrix showed alterations after ultraviolet-B (UVB) exposure (Guo et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sang et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2012\u003c/span\u003e). Exposure to UVB resulted in heightened sensitivity in \u003cem\u003eT. castaneum\u003c/em\u003e, leading to delayed metamorphosis, extended growth periods, and smaller pupal sizes. Researchers suggest that changes in endocrine signaling represent an adaptive physiological strategy in response to UVB exposure (Sang et al. \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Furthermore, cuticle properties of \u003cem\u003eT. castaneum\u003c/em\u003e larvae exposed to UVA changed, with increased exposure time leading to blurred boundaries of underlying epidermal cells on the dorsal surface, increased secretions deposited up to the epidermal cells, thickening of the exocuticle, and enlargement of the electron-dense outside region of the exocuticle (Liu et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). These studies indicated that \u003cem\u003eT. castaneum\u003c/em\u003e, living in low-UV environment, has developed various adaptation strategies in response to acute UV stress.\u003c/p\u003e \u003cp\u003eMicrobes are integral to ecosystems, exerting a profound influence on complex multicellular organisms and facilitating host adaptation (Waidele et al. \u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Du et al. \u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Deng et al. \u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e2023\u003c/span\u003e; Sessitsch et al. \u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Certainly, insect microbiomes also play a role in the adaptation of hosts facing environmental disruptions (Soen \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Shah et al. \u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e2024\u003c/span\u003e). For instance, the gut microbiome is quite important for insects that feed on woods due to its ability to digest lignocellulose (Auer et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Schwarz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Microbiota such as \u003cem\u003eWolbachia\u003c/em\u003e exhibited potential reproductive manipulation in insects (Joanne et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e). Additionally, alterations in bacterial community in invasive leaf miners \u003cem\u003eLiriomyza\u003c/em\u003e spp. contributed to host invasion and adaptation (Zhu et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). On account of the benefits of symbiotic bacteria, it interested us how bacteria within \u003cem\u003eT. castaneum\u003c/em\u003e aids in coping with UV stress.\u003c/p\u003e \u003cp\u003e16S rRNA amplicon sequencing is a technique commonly used for microbial species identification, involving the selection of variable regions, PCR amplification using universal primers for conservative regions, and subsequent sequencing analysis. This method has been widely used, emerging as a pivotal tool for studying the microbial community composition and structure (Caporaso et al. \u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Christensen et al. \u003cspan citationid=\"CR11\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Kameoka et al. \u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e2021\u003c/span\u003e). By using 16S rRNA amplicon sequencing, interactions among insects, microbiome and environments have been analyzed. Factors such as different food sources (Wang et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Yuan et al. \u003cspan citationid=\"CR63\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), developmental stages (Wang et al. \u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e2011\u003c/span\u003e; Yun et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2014\u003c/span\u003e), habitats (Yun et al. \u003cspan citationid=\"CR64\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Nobles and Jackson \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e2020\u003c/span\u003e), as well as stressors such as high temperature and pesticides influence the insect microbiome (Sun et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zeng et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Therefore, we attempted to investigate the role of microbiome within \u003cem\u003eT. castaneum\u003c/em\u003e in response to UV stress by employing 16S rRNA amplicon sequencing. UV radiation encompasses UVA (315\u0026ndash;400 nm), UVB (280\u0026ndash;315 nm), and UVC (200\u0026ndash;280 nm); UVC is primarily absorbed by the Earth\u0026rsquo;s atmosphere, leaving UVB (5% \u0026minus;\u0026thinsp;10%) and UVA (90% \u0026minus;\u0026thinsp;95%) as the main components reaching the Earth\u0026rsquo;s surface (Saucedo et al. \u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sproul 2013). Studies revealed that UV radiation can alter human microbiome, not only in skin (Burns et al. \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e2019\u003c/span\u003e), but also in gut (Bosman et al. \u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Rungjang et al. \u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Building on the above knowledge, we investigated the diversity of the bacterial communities within \u003cem\u003eT. castaneum\u003c/em\u003e following exposure to UVA and UVB for different durations, and to elucidate the role of the bacteria in insects living in low-UV environments.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Materials and methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003eInsects rearing\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003e \u003cem\u003eT. castaneum\u003c/em\u003e was reared on an artificial diet (5% yeast supplemented with whole-wheat flour) at 30\u0026deg;C under 60\u0026thinsp;\u0026plusmn;\u0026thinsp;2% relative humidity in constant darkness. Approximately 200 adults (1\u0026ndash;7 days old) laid eggs in flour for one hour, and the eggs were collected and transferred to a new diet after separation with a 60-mesh sieve. The larvae developed to the final instar stage (20-day-old) were used in the study.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003c/div\u003e\n\u003ch3\u003eTreatments with UVA and UVB irradiation\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eThe UVA treatment was manipulated by using 365 nm (wavelength peak of emission spectrum) light-emitting diode light (20W, Shenzhen Xinhongxian Photoelectric Technology Co., Ltd., Shenzhen, China). For UVB treatment, it was manipulated by using UV light (UV-B8W29T5, FSL, Foshan, China) emitting spectrum at wavelength peak of 308 nm. Before treatment, the flour on larvae surface was cleaned with sterile water. Larvae subjected to UV treatment received either UVA or UVB irradiation for durations of 20, 40, and 60 min, respectively. The illumination intensity was measured at 300 \u0026micro;W/cm\u003csup\u003e2\u003c/sup\u003e using a UV light meter (TAINA TN-2340, Taiwan, China). Treatment in darkness for 60 min was set as control (CK). Following irradiation or darkness treatments, larvae were continuously reared in darkness. Study on \u003cem\u003eT. castaneum\u003c/em\u003e larvae proposed that surface sterilization has minimal impact on microbial load and thus collected samples without dissection nor surface sterilization to obtain the overall microbiome under different treatments (Korša et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Even so, to eliminate the impacts from flour and microbiota on the surface, the larvae were immersed in 70% ethanol immersion for one minute, and then rinsed twice with sterile water after 24 h of feeding in darkness. Subsequently, larvae were rapidly frozen using liquid nitrogen and stored in a -80℃ refrigerator until DNA extraction. Samples subjected to UVA treatments for different durations were labeled as A20, A40 and A60; while samples subjected to UVB treatments were labeled as B20, B40 and B60, respectively. Each treatment included five biological replicates, with each replicate consisting of 20 individuals.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e\n\u003ch3\u003eDNA extraction, 16S rRNA amplification, library preparation and sequencing\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eTotal genome DNA was extracted using CTAB method. DNA concentration and purity was monitored on 1% agarose gels. According to the concentration, DNA was diluted to 1ng/\u0026micro;L using sterile water. Polymerase chain reaction amplification (PCR) was carried out for V3 to V4 region of the 16S rRNA, with 15 \u0026micro;L of Phusion\u0026reg; High-Fidelity PCR Master Mix (New England Biolabs); 0.2 \u0026micro;M of forward (341F: CCTAYGGGRBGCASCAG) and reverse (806R: GGACTACNNGGGTATCTAAT) primers, and about 10 ng template DNA. Thermal cycling consisted of initial denaturation at 98℃ for 1 min, followed by 30 cycles of denaturation at 98℃ for 10 s, annealing at 50℃ for 30 s, and elongation at 72℃ for 30 s, finally 72℃ for 5 min. Mix same volume of 1\u0026times; loading buffer (contained SYB green) with PCR products and operate electrophoresis on 2% agarose gel for detection. PCR products was mixed in equidensity ratios. Then, mixture PCR products was purified with Qiagen Gel Extraction Kit (Qiagen, Germany). Sequencing libraries were generated using TruSeq\u0026reg; DNA PCR-Free Sample Preparation Kit (Illumina, USA) following manufacturer's recommendations and index codes were added.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003eThe library quality was assessed on the Qubit@ 2.0 Fluorometer (Thermo Scientific) and Agilent Bioanalyzer 2100 system. The library was sequenced on Illumina NovaSeq6000 platform and 250 bp paired-end reads were generated.\u003c/p\u003e\n\u003ch3\u003eBioinformatics and statistical analysis\u003c/h3\u003e\n\u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003ePaired-end reads was assigned to samples based on their unique barcode and truncated by cutting off the barcode and primer sequence. Then, the paired-end reads were merged using FLASH (V1.2.7, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://ccb.jhu.edu/software/FLASH/\u003c/span\u003e\u003cspan address=\"http://ccb.jhu.edu/software/FLASH/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Magoč and Salzberg \u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and raw tags were obtained. High-quality clean tags were obtained by quality filtering on the raw tags (Bokulich et al. \u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), according to the QIIME (V1.9.1, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://qiime.org/scripts/split_libraries_fastq.html\u003c/span\u003e\u003cspan address=\"http://qiime.org/scripts/split_libraries_fastq.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) quality controlled process (Caporaso et al. \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e2010\u003c/span\u003e). The tags were compared with the reference database (Silva database, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.arb-silva.de/\u003c/span\u003e\u003cspan address=\"https://www.arb-silva.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) using UCHIME algorithm (UCHIME Algorithm, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.drive5.com/usearch/manual/uchime_algo.html\u003c/span\u003e\u003cspan address=\"http://www.drive5.com/usearch/manual/uchime_algo.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to detect chimera sequences (Edgar et al. \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e2011\u003c/span\u003e), and then the chimera sequences were removed (Haas et al. \u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e2011\u003c/span\u003e). Then the effective tags finally obtained.\u003c/p\u003e \u003cp\u003eSequences with \u0026ge;\u0026thinsp;97% similarity were assigned to the same Operational Taxonomic Units (OTUs), analyzed by Uparse software (Uparse v7.0.1001, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://drive5.com/uparse/\u003c/span\u003e\u003cspan address=\"http://drive5.com/uparse/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) (Edgar \u003cspan citationid=\"CR20\" class=\"CitationRef\"\u003e2013\u003c/span\u003e), and representative sequence for each OTU was screened for further annotation. For each representative sequence, the Silva Database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.arb-silva.de/\u003c/span\u003e\u003cspan address=\"http://www.arb-silva.de/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) was used based on Mothur algorithm to annotate taxonomic information (Quast et al. \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e2013\u003c/span\u003e). Multiple sequence alignments were conducted using the MUSCLE software (Version 3.8.31, \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttp://www.drive5.com/muscle/\u003c/span\u003e\u003cspan address=\"http://www.drive5.com/muscle/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) to study phylogenetic relationship of different OTUs and the difference of the dominant species in different samples (Edgar \u003cspan citationid=\"CR19\" class=\"CitationRef\"\u003e2004\u003c/span\u003e). OTUs abundance information were normalized using a standard of sequence number corresponding to the sample with the least sequences. Subsequent analysis of alpha diversity and beta diversity were all performed basing on this output normalized data.\u003c/p\u003e \u003cp\u003eAlpha diversity is applied in analyzing complexity of species diversity for a sample through 6 indices, including Observed-species, Chao1, Shannon, Good-coverage. All these indices in our samples were calculated with QIIME (Version 1.7.0) and displayed with R software (Version 2.15.3).\u003c/p\u003e \u003cp\u003eBeta diversity analysis was used to evaluate differences of samples in species complexity. Beta diversity on weighted Unifrac was calculated by QIIME software (Version 1.9.1). Principal coordinate analysis (PCoA) analysis was displayed by WGCNA package, stat packages and ggplot2 package in R software (Version 2.15.3). Unweighted Pair-group Method with Arithmetic Means (UPGMA) Clustering was performed as a type of hierarchical clustering method to interpret the distance matrix using average linkage and was conducted by QIIME software (Version 1.9.1). Linear discriminant analysis of effect size (LEfSe) (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.omicstudio.cn/tool\u003c/span\u003e\u003cspan address=\"https://www.omicstudio.cn/tool\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e.) was used to determine OTUs that discriminate among the microbiome with an LDA score greater than 2. Function prediction of microbiome was performed by PICRUSt with reference to Kyoto Encyclopedia of Genes and Genomes (KEGG) database (Langille et al. \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e2013\u003c/span\u003e).\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003eAnalysis of 16S rRNA amplicon sequencing\u003c/h2\u003e \u003cp\u003e \u003cdiv class=\"BlockQuote\"\u003e \u003cp\u003eIn this study, seven sets of data from 35 samples were acquired. A total of 3,588,114 raw paired-end reads were obtained, from which 2,278,846 effective tags were generated (Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The average read length ranged from 392 to 425 nt. The effective tags were clustered into 1,928 OTUs, of which 1,564 OTUs (81.12%) could be annotated to the Silva database. Among the annotated OTUs, 81.12% OTUs were annotated at kingdom level, 53.63% at phylum level, 52.59% at class level, 51.24% at order level, 48.13% at family level, 34.96% at genus level, and 11.10% at species level. The OTUs were further categorized into 34 phyla, 80 classes, 166 orders, 260 families, 374 genera, and 210 species.\u003c/p\u003e \u003c/div\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eDiversity of bacterial communities within\u003c/b\u003e \u003cb\u003eT. castaneum\u003c/b\u003e \u003cb\u003eexposed to UVA and UVB\u003c/b\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eThe good\u0026rsquo;s coverage index of all samples, which reflects the sequencing depth truly, exceeded 0.9999 (Table S2). The rarefaction curve trend appeared flat (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ea), indicating sequencing data is large enough, and more data will not result in more OTUs. It can reflect the majority of microbial information of samples. This suggested that the sequencing depth has covered all species of the samples basically.\u003c/p\u003e\u003cp\u003eThe rank abundance reflected the abundance and evenness of OTUs in the samples (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003eb). The width and smoothness of the curve indicated the abundance and evenness, respectively. Across all larval samples, the quantities of observed species in microbiome were statistically insignificant (Wilcoxon test, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.05) (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ec, Table S2). The shannon indices revealed differences in species diversity among the sample groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003ed, Table S2). The diversity of microbiome in the A60 group was higher than in the A20, B20, and CK groups (Wilcoxon test, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05). Besides, the A40 group showed higher diversity than the A20 group while the B60 group exhibited higher diversity than the A20 and B20 groups (\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003ePCoA and UPGMA clustering analysis based on weighted Unifrac distance were employed to analyze the diversity of bacterial communities within \u003cem\u003eT. castaneum\u003c/em\u003e exposed to UVA and UVB irradiation (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e). The diversity analysis based on weighted Unifrac distance revealed significant difference between group CK and A60 (Wilcoxon test, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05), as well as between A60 and A40, A60 and B20, respectively (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ea). The cluster analysis at phylum level showed that CK and B20, A20 and B40, A40 and B60 formed distinct branches (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ec). There was no clear separation observed between CK group and other groups treated by UV irradiation (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e).\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eComparison of bacterial communities within T.\u003c/b\u003e \u003cb\u003ecastaneum\u003c/b\u003e \u003cb\u003eexposed to UVA and UVB\u003c/b\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo investigate the exact variation on bacterial communities within \u003cem\u003eT. castaneum\u003c/em\u003e exposed to UVA and UVB irradiation, analysis at different levels of the top 10 bacteria was conducted (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e). Proteobacteria and Cyanobacteria were dominant taxa at phylum level, followed with Firmicutes (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003ea). When exposed to UVA for 20min, \u003cem\u003eT. castaneum\u003c/em\u003e exhibited the highest relative abundance of Proteobacteria (74.00\u0026thinsp;\u0026plusmn;\u0026thinsp;2.00%), significantly higher than in A40, A60 and B60 groups (Student\u0026rsquo;s t test, P\u0026thinsp;\u0026lt;\u0026thinsp;0.05), while concurrently displaying a lower abundance of Cyanobacteria (19.23\u0026thinsp;\u0026plusmn;\u0026thinsp;3.62%) (Fig. S2a). Additionally, the relative abundance of Proteobacteria in B40 group was also higher than in A40 and A60 groups (Fig. S2a). At the genus level, \u003cem\u003eIzhakiella\u003c/em\u003e, \u003cem\u003eunidentified Mitochondria\u003c/em\u003e, and \u003cem\u003eunidentified Chloroplast\u003c/em\u003e were dominant constituents in the bacterial communities (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). The relative abundance of \u003cem\u003eunidentified Chloroplast\u003c/em\u003e was lowest in the A20 group, registering at 19.15\u0026thinsp;\u0026plusmn;\u0026thinsp;3.60%, significantly lower than relative abundance in A40 (44.20\u0026thinsp;\u0026plusmn;\u0026thinsp;3.37%), A60 (36.67\u0026thinsp;\u0026plusmn;\u0026thinsp;6.09%) and B60 (41.07\u0026thinsp;\u0026plusmn;\u0026thinsp;2.70%) groups (Fig. S2b). The abundance of \u003cem\u003eunidentified Mitochondria\u003c/em\u003e remained relatively stable across these samples, ranging from 30.07\u0026ndash;40.63%. Apart from the dominant compositions, \u003cem\u003ePseudomonas\u003c/em\u003e occupied a higher proportion in CK group; \u003cem\u003eEnterococcus\u003c/em\u003e in A20 and B40; \u003cem\u003eWeissella\u003c/em\u003e in A60; \u003cem\u003ePleionea\u003c/em\u003e in A40; and \u003cem\u003eParacoccus\u003c/em\u003e in B20; however, no statistically significant difference was found in relative abundance of these genera among the sample groups (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003eb). To identify potential biomarkers for each group, LEfSe analysis to simultaneously identify dominant bacteria was conducted. The result showed that Proteobacteria was dominant in A20 group (LDA\u0026thinsp;\u0026gt;\u0026thinsp;4) (Kruskal-Wallis test, Wilcoxon test, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05) (Fig. S3).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003cb\u003eFunction prediction of bacteria within T.\u003c/b\u003e \u003cb\u003ecastaneum\u003c/b\u003e \u003cb\u003eexposed to UVA and UVB\u003c/b\u003e\u003cdiv class=\"BlockQuote\"\u003e\u003cp\u003eTo further study the function of bacteria in \u003cem\u003eT. castaneum\u003c/em\u003e, the abundance of gene encoded by bacteria annotated on KEGG pathway were performed. The KEGG pathway annotation showed that a majority of genes were annotated on Environmental Information Processing, Genetic Information Processing and Metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). Within these categories, pathways including membrane transport, replication and repair, amino acid metabolism, energy metabolism and carbohydrate metabolism, exhibited the highest numbers of gene enrichments (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003ea). The relative abundance annotated on KEGG pathways at level1 and top 10 pathways at level 2 were analyzed among the sample groups. Most pathways displayed no significant difference, except for pathway of metabolism of cofactors and vitamins, and energy metabolism (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003eb, c). The analysis of other pathways at level2 showed that A20 had a lower relative abundance annotated in metabolic diseases, enzyme families (Fig. S4). Besides, cluster analysis of top 35 enriched KEGG pathways was performed (Fig. S4a). The clustering result differed from UPGMA clustering analysis about diversity of bacterial communities (Fig. \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003ec). The CK and B20 groups were clustered together, and A60 showed a relatively close relation; the clustering of B40, B60 and A40 had a similar effect, with A20 as an outgroup (Fig. S4a).\u003c/p\u003e\u003c/div\u003e\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e"},{"header":"Discussion","content":"\u003cp\u003eUV radiation has impacted on the evolutionary course of all forms of life, from microorganisms to humans (Rai et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). As previously mentioned, the beetles, \u003cem\u003eT. castaneum\u003c/em\u003e have developed various adaptation strategies in response to UV stress (Guo et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sang et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Microbiome of insect colonizes on the insect exoskeleton, in the gut and hemocoel, and within insect cells, playing important role in nutrition, protection, and detoxification (Douglas \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e2015\u003c/span\u003e). Moreover, it facilitates host adaptation (Joanne et al. \u003cspan citationid=\"CR30\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Auer et al. \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zhu et al. \u003cspan citationid=\"CR67\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Schwarz et al. \u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). To our knowledge, there is a gap in studying the effects of UV irradiation on insect microbiome and the role of microbes in developing adaptation strategies to UV stress for insects. Therefore, we utilized 16S rRNA amplicon sequencing to investigate the diversity of bacterial communities within \u003cem\u003eT. castaneum\u003c/em\u003e after exposure to UVA and UVB for different durations, and the role of bacteria within \u003cem\u003eT. castaneum\u003c/em\u003e when living in low-UV environment. As results exhibited above, the significant differences observed in this study were limited, there was no clear separation between CK group and other groups treated with UV irradiation. It was challenging to establish a clear relation between UV irradiation and bacteria within \u003cem\u003eT. castaneum\u003c/em\u003e larvae. Consequently, we deliberated on the potential influence of UV irradiation on the bacterial communities within \u003cem\u003eT. castaneum\u003c/em\u003e larvae. We propose the viewpoint that the bacteria which aids in coping with UVA and UVB stress had been lost in the evolution due to the low-UV habitats; and current bacteria within \u003cem\u003eT. castaneum\u003c/em\u003e may have limited functionality in contributing to develop host adaptation strategies to acute UV stress.\u003c/p\u003e \u003cp\u003eIn this study, while the species richness of samples was statistically insignificant, the relative abundance of bacterial communities varied significantly among the samples. This can be attributed to the fact that only external physical factor was taken in this study, without introducing additional bacterial species such as changes in food source. The dominant bacterial communities observed in samples were Proteobacteria (45.59\u0026ndash;74.00%), Cyanobacteria (19.23\u0026ndash;44.5%) and Firmicutes (0.45\u0026ndash;5.29%) at phylum level. Researches on microbiome within \u003cem\u003eT. castaneum\u003c/em\u003e had also highlighted Proteobacteria as a dominant bacterial community, which aligns with our findings. However, varying compositions were reported, with some including Firmicutes and Actinobacteriota (Korša et al.2022; Wang \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). It's worth noting that Korša et al. excluded Cyanobacteria from their study, attributing their presence to the flour (Korša et al.2022), and the low abundance of Cyanobacteria in \u003cem\u003eT. castaneum\u003c/em\u003e adult may be attributive to starvation treatment (Wang \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). Similarly, study on \u003cem\u003eAntheraea pernyi\u003c/em\u003e showed a significant percentage of Cyanobacteria (85.90% and 93.82%) in the midgut and midgut contents, alongside Firmicutes and Proteobacteria (Zhang et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e; Wang et al. \u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). But Zhang et al. (\u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e) considered the result was caused by the limitations of research methods, suggesting that a large number of chloroplast nucleic acids in the gut of phytophagous Lepidoptera larvae can be amplified by universal primers of bacterial 16S rRNA gene (Zhang et al. \u003cspan citationid=\"CR66\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). In spite of this, the portion and variation of Cyanobacteria and unidentified Chloroplast led to a unneglected problem in this study. Appetite alteration was observed in various organisms, causing a decrease of appetite in juvenile European seabass (\u003cem\u003eDicentrarchus labrax\u003c/em\u003e) (Alves et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2021\u003c/span\u003e) and Gilthead Seabream (\u003cem\u003eSparus aurata\u003c/em\u003e) (Alves et al. 2020), and an increase in mice and human males (Parikh et al. \u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e2022\u003c/span\u003e, \u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Exposure to high dose of UVB for 120min led to a decrease in the amount of faeces in \u003cem\u003eGalleria mellonella\u003c/em\u003e (Sabockyte et al. \u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e)[62]. And the higher levels of viable bacteria observed in UVB-exposed larvae may be due to impaired antimicrobial peptide synthesis, as suggested by Sabockyte et al. (\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e2023\u003c/span\u003e). Furthermore, certain cyanobacteria are known to respond to light. These cyanobacteria produce mycosporine amino acids that absorb UV radiations and confer resistance to several abiotic stresses, they can also transfer genes to plants and animals, providing UV protection (Carletti et al. \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e2014\u003c/span\u003e; Rai et al. \u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). However, these specific cyanobacteria were not identified in this study. Therefore, while the presence of cyanobacteria in the larvae may be attributed to diet, the variation in cyanobacteria levels could be influenced by remote effects stemming from alterations in appetite or other unknown impacts of UV irradiation.\u003c/p\u003e \u003cp\u003eIn this study, apart from \u003cem\u003eunidentified Chloroplast\u003c/em\u003e (Cyanobacteria), the dominant genera observed were \u003cem\u003eIzhakiella\u003c/em\u003e (Enterobacterales), \u003cem\u003eunidentified Mitochondria\u003c/em\u003e (Rickettsiales), both belonging to Proteobacteria. The relative abundance of Proteobacteria was higher in A20 and B40 groups compared to A40 and A60 groups, but there was no significant difference in relative abundance of \u003cem\u003eIzhakiella\u003c/em\u003e (Enterobacterales) and \u003cem\u003eunidentified Mitochondria\u003c/em\u003e (Rickettsiales). These results suggested that UV irradiation had a minor effect on relative abundance of Proteobacteria, but did not significantly affect the two dominant genera within Proteobacteria. This indicated that the alterations observed in Proteobacteria abundance due to UV irradiation were caused by other genera within the microbial community. Beyond that, the dominant genera observed in other studies differed from our findings, which was in larvae and adults of \u003cem\u003eT. castaneum\u003c/em\u003e, respectively (Korša et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). This may be attributed to the differences in population sources, sample collection methods and even the rearing conditions of \u003cem\u003eT. castaneum\u003c/em\u003e. An important factor to note is the light-dark cycle used in breeding beetles. In our study, the beetles used for experiments were kept in constant darkness, whereas other studies reared beetles under a light-dark cycle of 12:12 or 16:8 (Korša et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). The discrepancy of luminous environments prompts us to analyze the diversity of microbial community in insects living under different light conditions. Among the top 10 most abundance genera, Pseudomonas and Enterococcus were common across our study and the mentioned studies (Korša et al. \u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e2022\u003c/span\u003e; Wang \u003cspan citationid=\"CR62\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). These genera may play crucial roles in various physiological processes beyond responding to UV stress. Further research is warranted to identify crucial bacteria that respond to UV stress and contribute to host adaptation.\u003c/p\u003e \u003cp\u003eLikewise, relative abundance of gene encoded by bacteria and annotated on KEGG pathways at level1 and top 10 pathways at level2 were analyzed between the sample groups. The KEGG pathway annotation revealed that most genes were annotated on membrane transport (Environmental Information Processing), replication and repair (Genetic Information Processing), amino acid metabolism, energy metabolism and carbohydrate metabolism (Metabolism). However, the majority of these pathways showed no significant differences between the groups. Studies demonstrated that nocturnal insects coordinated energy metabolism and antioxidant activity under light stress by lysine succinylation (Huang et al. \u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e2021\u003c/span\u003e), and larvae of green tree frog (\u003cem\u003eLitoria caerulea\u003c/em\u003e) exhibited a higher rates of energy expenditure when exposed to high levels of UV radiation compared to those exposed to lower UV levels (Cramp et al. \u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). Although differences in energy metabolism were detected in UV irradiation groups, these differences were not observed when compared to control groups.\u003c/p\u003e \u003cp\u003eResearches have suggested that stressors such as high temperature and pesticide have effects on insect microbiome (Sun et al. \u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e2017\u003c/span\u003e; Zeng et al. \u003cspan citationid=\"CR65\" class=\"CitationRef\"\u003e2020\u003c/span\u003e). However, our investigation into the bacteria of \u003cem\u003eT. castaneum\u003c/em\u003e subjected to UV irradiation revealed minor effects, with no significant differences observed compared to the CK group. This result leads to the assumption that insects living in low-UV environment may have undergone a loss of crucial bacteria responsible for coping with UV stress over long-term evolution. Additionally, analyzing the microbial community diversity in insects living at various altitudes with different UV intensities may offer new insights. Nevertheless, despite similarities in living conditions, the composition of microbiomes is notably different, even among insects similar to \u003cem\u003eT. castaneum\u003c/em\u003e. This underscores the need for further research to compare microbiome differences in insects under various light and UV environments. In studies focused on UV irradiation effects on \u003cem\u003eT. castaneum\u003c/em\u003e, demonstrated their ability to develop adaptation strategies, as evidenced by the regulation of stress-responsive gene expression and structural alterations (Guo et al. \u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e2019\u003c/span\u003e; Sang et al. \u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e2012\u003c/span\u003e, \u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e2016\u003c/span\u003e; Liu et al. \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e2018\u003c/span\u003e). Yet in this study, no bacteria exhibited potential contributions to host adaptation under UV stress. Considering the rearing conditions of \u003cem\u003eT. castaneum\u003c/em\u003e, the strong capability to utilize UV or resist UV-induced damage is likely costly. Bacterial symbionts, with their higher mutation rates and susceptibility to gene loss, may inadvertently lose essential genes for their host, potentially leading to replacement by other symbionts (McCutcheon and Moran \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e2010\u003c/span\u003e; Coolen et al. 2022). Moreover, structural alterations in \u003cem\u003eT. castaneum\u003c/em\u003e exposed to UV irradiation, such as increased secretions deposited up to the epidermal cells and thickened exocuticle, could reduce the likelihood of receiving UV signaling for bacteria within \u003cem\u003eT. castaneum\u003c/em\u003e. Thus, the functional role of bacteria in resisting UV stress appears to be costly for both bacteria and \u003cem\u003eT. castaneum\u003c/em\u003e. While the assumption of losing crucial bacteria contributing to UV resistance is plausible, further research is essential to unravel the commonalities in microbiome of photophobic insects, and to verify the assumption that photophobic insects adapted to prolonged darkness may abandon microbiota that respond to UV stress.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eA\u003c/strong\u003e\u003cstrong\u003euthor contribution\u0026nbsp;\u003c/strong\u003eFei-Feng Wang: conceptualization; formal analysis; writing \u0026ndash; original draft. Min-Er Li: investigation; formal analysis; data curation. Lu-Lu Dong: investigation; formal analysis. Zhao-Kang Liu: investigation; formal analysis. Yu-Die Xia: investigation. Lin Yu: writing \u0026ndash; review and editing. Bao-Li Qiu: supervision; writing \u0026ndash; review and editing. Wen Sang: conceptualization; funding acquisition; writing \u0026ndash; review and editing.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u0026nbsp;\u003c/strong\u003eThis\u0026nbsp;work was supported by\u0026nbsp;the\u0026nbsp;National Natural Science Foundation of China (31701793), the National Key R \u0026amp; D Program of China (2023YFD1400700), the Natural Science Foundation of Guangdong Province (2023A1515030219), and the Science and Technology Program of Guangzhou (202206010042).\u003cstrong\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eD\u003c/strong\u003e\u003cstrong\u003eata availability\u0026nbsp;\u003c/strong\u003eThe data that support the findings of this study are available at NCBI database (Accession No. PRJNA1107833).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthics approval and consent to participate\u0026nbsp;\u003c/strong\u003eNot applicable.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent to participate\u0026nbsp;\u003c/strong\u003eAll authors approved the final version.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u0026nbsp;\u003c/strong\u003eThe manuscript has not been published previously in the same or very similar form in any other journal. The manuscript is not currently under consideration in other journals.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCompeting interests\u0026nbsp;\u003c/strong\u003eThe authors declare no competing interests.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eAlves RN, Justo MSS, Laranja JLQ, Alarcon JF, Al Suwailem A, Agust\u0026iacute; S (2021) Exposure to natural ultraviolet B radiation levels has adverse effects on growth, behavior, physiology, and innate immune response in juvenile European seabass (\u003cem\u003eDicentrarchus labrax\u003c/em\u003e). 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Microbiol Spectr 10:e00266\u0026ndash;e00222. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1128/spectrum.00266-22\u003c/span\u003e\u003cspan address=\"10.1128/spectrum.00266-22\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Tribolium castaneum, Photophobic insect, Ultraviolet stress, Microbiome, 16S rRNA, Adaptation strategy","lastPublishedDoi":"10.21203/rs.3.rs-5300393/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-5300393/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e \u003cem\u003eTribolium castaneum\u003c/em\u003e (Herbst), which resides in shaded areas avoiding daylight, has developed various adaptation strategies to cope with ultraviolet (UV) stress. In this study, we utilized 16S rRNA amplicon sequencing to assess the diversity of the bacterial communities within \u003cem\u003eT. castaneum\u003c/em\u003e following exposure to ultraviolet-A and ultraviolet-B for different durations, and to elucidate the role of microbiome in host response to UV stress. This study revealed that UV irradiation affected the relative abundance of bacterial community within \u003cem\u003eT. castaneum\u003c/em\u003e, rather than its species richness. The significant differences were observed in the relative abundance of Proteobacteria and Cyanobacteria, among the comparison of UV irradiation groups at phylum level. Most genes coded by bacteria were annotated on membrane transport, replication and repair, amino acid metabolism, energy metabolism and carbohydrate metabolism with reference to Kyoto Encyclopedia of Genes and Genomes database. However, the significant differences identified in this study were limited, making it challenging to establish a clear relationship between UV irradiation and the bacteria within \u003cem\u003eT. castaneum\u003c/em\u003e larvae. Consequently, we propose the viewpoint that the role of bacteria in contributing \u003cem\u003eT. castaneum\u003c/em\u003e against UV stress may have been diminished during their development due to the low-UV rearing conditions.\u003c/p\u003e","manuscriptTitle":"Loss of helpful bacteria within Tribolium castaneum that aid in coping with UVA and UVB stress","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-11-26 12:17:17","doi":"10.21203/rs.3.rs-5300393/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"4e50178a-1e98-4029-a348-bb1aa09f2715","owner":[],"postedDate":"November 26th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-04-03T21:02:00+00:00","versionOfRecord":[],"versionCreatedAt":"2024-11-26 12:17:17","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-5300393","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-5300393","identity":"rs-5300393","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}