Strong microbiome disruption reduces damselfly survival, and subsequent pathogen exposure tends to increase mortality across metamorphosis

Strong microbiome disruption reduces damselfly survival, and subsequent pathogen exposure tends to increase mortality across metamorphosis | Authorea try { document.documentElement.classList.add('js'); } catch (e) { } var _gaq = _gaq || []; _gaq.push(['_setAccount', 'G-8VDV14Y67G']); _gaq.push(['_trackPageview']); (function() { var ga = document.createElement('script'); ga.type = 'text/javascript'; ga.async = true; ga.src = ('https:' == document.location.protocol ? 'https://ssl' : 'http://www') + '.google-analytics.com/ga.js'; var s = document.getElementsByTagName('script')[0]; s.parentNode.insertBefore(ga, s); })(); Skip to main content Preprints Collections Wiley Open Research IET Open Research Ecological Society of Japan All Collections About About Authorea FAQs Contact Us Quick Search anywhere Search for preprint articles, keywords, etc. Search Search ADVANCED SEARCH SCROLL This is a preprint and has not been peer reviewed. Data may be preliminary. 4 August 2025 V1 Latest version Share on Strong microbiome disruption reduces damselfly survival, and subsequent pathogen exposure tends to increase mortality across metamorphosis Authors : Charlotte Theys 0000-0002-8247-3228 [email protected] , Julie Verheyen , Alessio Cocco 0000-0002-7932-8687 , Ellen Decaestecker , and Robby Stoks Authors Info & Affiliations https://doi.org/10.22541/au.175431308.88366738/v1 217 views 155 downloads Contents Abstract Information & Authors Metrics & Citations View Options References Figures Tables Media Share Abstract Microbiomes are increasingly recognized as key contributors to host fitness, yet their role in mediating stressor effects, especially across metamorphosis, remain poorly understood. To address this knowledge gap, we strongly reduced the gut microbiome of Ischnura elegans damselfly larvae using antibiotics followed by inoculation with a donor gut microbiome or not, and afterwards exposed the larvae to the pathogen Escherichia coli . Both host fitness and gut microbiome diversity and community composition were assessed during the larval and adult life stages. Despite marked differences in gut microbiome community composition between both life stages, partial retention of larval taxa in adult microbiota suggests incomplete microbiome turnover in these hemimetabolous insects. Furthermore, microbiome disruption significantly increased larval mortality, an effect mitigated by microbiome inoculation, underscoring the functional importance of microbial associations in damselflies. Moreover, pathogen exposure elevated larval mortality and tended to induce delayed mortality in the adult stage, revealing carry-over effects across metamorphosis. Yet, we did not find evidence of the gut microbiome mediating these carry-over effects. Together, our results highlight the critical role of the microbiome in determining host fitness, and the importance of considering both immediate and delayed stressor effects in animals with complex life cycles. Strong microbiome disruption reduces damselfly survival, and subsequent pathogen exposure tends to increase mortality across metamorphosis Abstract Microbiomes are increasingly recognized as key contributors to host fitness, yet their role in mediating stressor effects, especially across metamorphosis, remain poorly understood. To address this knowledge gap, we strongly reduced the gut microbiome of Ischnura elegans damselfly larvae using antibiotics followed by inoculation with a donor gut microbiome or not, and afterwards exposed the larvae to the pathogen Escherichia coli . Both host fitness and gut microbiome diversity and community composition were assessed during the larval and adult life stages. Despite marked differences in gut microbiome community composition between both life stages, partial retention of larval taxa in adult microbiota suggests incomplete microbiome turnover in these hemimetabolous insects. Furthermore, microbiome disruption significantly increased larval mortality, an effect mitigated by microbiome inoculation, underscoring the functional importance of microbial associations in damselflies. Moreover, pathogen exposure elevated larval mortality and tended to induce delayed mortality in the adult stage, revealing carry-over effects across metamorphosis. Yet, we did not find evidence of the gut microbiome mediating these carry-over effects. Together, our results highlight the critical role of the microbiome in determining host fitness, and the importance of considering both immediate and delayed stressor effects in animals with complex life cycles. Keywords: Aquatic invertebrates, Microbiota, Life stages, Microbiome reduction, Pathogen tolerance, Transplant Highlights • Microbiome community differed between life stages • No complete microbiome turnover across metamorphosis • Microbiome disruption reduced larval survival with recovery through inoculation • The pathogen reduced larval survival with adverse carry-over effects on adult survival • No evidence of the gut microbiome mediating the carry-over effects Graphical abstract Introduction In many animals, development proceeds through distinct life stages often separated by metamorphosis (Moran, 1994). A key challenge in life-history theory is to determine how stressors experienced during early life stages, can shape fitness in later life stages, especially across metamorphosis. Quantifying such carry-over effects is important as these are essential to assess the total fitness impact of a stressor (Stoks et al., 2022a). For example, in insects which undergo metamorphosis stressor exposure during the larval stage may result in negative carry-over effects into the adult stage, as early-life environmental conditions may influence trait expression across life stages and habitats (Moore and Martin, 2019; Rolff et al., 2019). Such carry-over effects of larval stressors into the adult stage are widespread and can take many forms, including decreased emergence success (Monteiro et al., 2019; Palmquist et al., 2008), reduced energy storage (Stoks et al., 2006a), increased wing malformations (Dinh et al., 2016a), lowered immune responses (Dinh et al., 2016a), decreased longevity (Mutamiswa et al., 2022), lowered heat tolerance (Mutamiswa et al., 2022), reduced body size (Niitepõld and Boggs, 2022), and even reduced survival and reproduction (De Block and Stoks, 2005; Lee et al., 2012; Relyea and Hoverman, 2003; Stoks et al., 2022b). Although many studies have demonstrated carry-over effects across metamorphosis, the underlying mechanisms, such as morphological (Dinh et al., 2016a, 2016b), physiological (Debecker et al., 2015; Stoks et al., 2006b), gene expression (Boone et al., 2013; Xie et al., 2015) or epigenetic changes (Metzger and Schulte, 2018), remain poorly understood. One potentially important but largely ignored mechanism underlying carry-over effects across metamorphosis might be the gut microbiome. The gut microbiome is increasingly recognized for its crucial role in shaping host fitness by influencing life history traits (e.g., mortality, development, growth rate), behaviour (e.g., activity) and physiology (e.g., immune functioning) (Gupta and Nair, 2020; Lynch and Hsiao, 2019; Macke et al., 2017; Peerakietkhajorn et al., 2016). Notably, one of the very few studies that directly examined the impact of microbiome disruption across metamorphosis showed that disturbing the microbiota of tadpoles decreased parasite resistance in adult amphibians (Knutie et al., 2017b). While studying microbiome effects across metamorphosis remains very rare, more studies across multiple taxa have demonstrated that a strong reduction of the gut microbiome, for example through antibiotic exposure, can negatively impact host fitness due to the loss of beneficial resident bacteria. For example, Daphnia magna requires a microbiome to survive, grow and reproduce, whereby the loss of their microbiome and following re-inoculation with a donor microbiome can restore the host’s functionalities (Peerakietkhajorn et al., 2016; Sison-Mangus et al., 2015). Likewise, the immune response of germ-free honeybees ( Apis mellifera ) (Tang et al., 2023) and butterflies ( Helicoverpa armigera ) (Tian et al., 2023) decreased following microbiome disruption but could be restored through specific bacterial inoculations. Also, in cotton stainers ( Dysdercus fasciatus ) and firebugs ( Pyrrhocoris apterus ), microbiome disruption through egg-surface sterilization increased mortality and reduced growth rates, whereby host fitness could be completely restored through inoculation with the original microbiome (Salem et al., 2013). Yet, such rigorous experimental testing of the microbiome’s effect on host fitness across metamorphosis is lacking so far. More general, the extent to which hosts depend on their microbiome remains largely unclear. Some studies suggest that several taxa, including dragonflies, may not rely on a microbiome at all (Hammer et al., 2019). Ideally, experiments should be conducted under ecologically relevant, stressful conditions, such as the presence of natural enemies, to fully capture potential microbiome contributions to host performance (Hammer et al., 2019). Such studies would also allow the first experimental testing whether larval stressors may affect adult host performance through effects on the gut microbiome. Increasing evidence indicates that environmental stressors can directly or indirectly affect the gut microbiome, potentially leading to negative carry-over effects on host fitness across metamorphosis. One notable example comes from a study where tadpoles, which were fed on a low quality diet, had an altered adult frog microbiota that decreased adult defences against parasites (Knutie et al., 2017a). In natural environments, pathogens may directly alter microbial abundance or community composition by resource competition with the resident microbes (Bénard et al., 2020; de Muinck et al., 2013; Dillon and Dillon, 2004), or indirectly affect the microbiome through disruption of host physiology, such as a lowered immunity or decreased niche availability for beneficial microbes (Hartman and Tringe, 2019; Monnin et al., 2016; Williams et al., 2016). One such pathogen, Escherichia coli , is abundant in natural aquatic systems (Leff and Lemke, 1998) and has been found to negatively affect insects, for example, by increasing energetic costs associated to immune defence (Freitak et al., 2009, 2007). When the gut microbiome is already disrupted, such as through antibiotic exposure, subsequent exposure to E. coli may exacerbate negative effects on host fitness, even across metamorphosis. However, introduced bacteria may provide partial functional compensation potentially buffering fitness loss under microbiome-depleted conditions (Peerakietkhajorn et al., 2016; Sison-Mangus et al., 2015), suggesting that the presence of E. coli could be more beneficial than the complete absence of gut bacteria. Directly relevant for microbiome-mediated carry-over effects is that the gut microbiome diversity and community composition have been found to often vary across life stages (Yun et al., 2014), certainly when different life stages inhabit different environments with distinct environmental microbial communities (Nobles and Jackson, 2020). In insects, metamorphosis from aquatic larvae to terrestrial adults, can involve major shifts in microbial communities. In some species, the gut microbiome completely renews during metamorphosis, as in Brithys crini moths (González-Serrano et al., 2020) and multiple mosquito species (Moll et al., 2001). Yet, in other insect species, certain bacterial taxa persist across metamorphosis, as seen in butterflies (Mereghetti et al., 2019), dragonflies (Nobles and Jackson, 2020), and different mosquito species (Juma et al., 2020; Sela et al., 2020; Wang et al., 2011). Consequently, disruption of the gut microbiome in the larval stage can therefore not only have immediate consequences for the larvae, but can potentially also carry over across metamorphosis and negatively affect the adults. For instance, gnotobiotic Aedes aegypti larvae that were exposed to different bacterial strains, resulted in differential impacts on adult survival (Giraud et al., 2021). In this study, we aimed to assess whether a strong reduction of the gut microbiome, here studied as the bacterial component of the living microorganisms in the gut, combined with exposure to the biotic stressor, E. coli , influences larval and adult fitness in I. elegans . To this end, I. elegans larvae were exposed to an antibiotic mixture to strongly reduce their gut microbiome, whereafter, only half of the larvae received a donor gut microbiome to allow immediate reassembly. Subsequently, larvae were exposed either to E. coli or to a solvent control. First, we expected that gut microbiome disruption and/or E. coli exposure would negatively impact larval fitness, with potential negative carry-over effects across metamorphosis on adult performance. Second, we expected the gut microbiome to differ between the life stages and to strongly diverge depending on whether larvae received a donor gut microbiome, with additional alterations caused by E. coli exposure due to microbial competition. Third, we predicted that the combination of a strong reduction of the gut microbiome and E. coli exposure would have stronger negative effects on fitness and gut microbiome community composition than either factor alone, due to reduced microbial resistance and resilience in the disrupted microbiome. Materials and methods Study species and pre-experimental rearing From shallow ponds around Leuven (50°53’42” N, 4°43’22” E; 50°51’45” N, 4°41’01” E; 50°50’28” N, 4°39’28” E), in total 25-30 mated I. elegans females were collected in mid-August 2022 and placed individually in plastic vials provided with a wet filter paper for oviposition. In the laboratory in Leuven (Belgium), eggs were placed in plastic cups containing 100 mL dechlorinated tap water and put in temperature-controlled incubators at a 20 °C water temperature and a 14:10 h light-dark cycle. Ten days post hatching, larvae were placed individually in plastic cups (5 cm height, 6 cm diameter) containing 90 mL dechlorinated tap water and fed ad libitum with Artemia nauplii from Monday till Friday. Experimental design The resident gut bacteria were strongly depleted in all larvae between one and three days after reaching the final instar whereafter half of the larvae were re-inoculated with a donor gut microbiome. Following, both groups of larvae were exposed to a solvent control or to the pathogen E. coli. This resulted in 4 treatment combinations: 2 gut microbiome treatments (absence vs. presence) × 2 E. coli treatments (absence vs. presence). Per treatment combination, 188 – 192 randomly chosen larvae were tested from the total set of mothers, of which 125 – 142 number of larvae per treatment combination were reared until the adult stage. An optimized gut microbiome re-inoculation assay for the study species was used, following Theys et al. (2025). The strong depletion of the resident gut microbiota of larvae was performed by exposing the larvae for two days ( during which they were not fed ) to a 40 mL antibiotic mixture, which was renewed after 24 h (50 mL plastic cups). The mixture consisted of ampicillin (200 mg/L; Sigma-Aldrich ampicillin trihydrate), kanamycin (100 mg/L; Sigma-Aldrich kanamycin sulphate from Streptomyces) and tetracycline (100 mg/L; Sigma-Aldrich tetracycline hydrochloride), dissolved in Milli-Q water. After the antibiotic exposure, larvae were washed in triplicate and placed in 50 mL sterile dechlorinated tap water (200 mL sterile closed jars). This method was shown to remove 99 % of the resident gut bacteria of the larvae (Theys et al., 2025) . Half of the larvae received a donor gut inoculum of which 100 µL was added to their medium. All larvae were fed an ad libitum amount of sterile Artemia nauplii. The d onor gut inoculum was obtained by dissecting I. elegans donor larvae of the same set of populations after they were washed in triplicate in sterile dechlorinated tap water. Donor guts were pooled in sterile Eppendorf tubes with 325 µL sterile Ringer solution per donor gut. From the pooled donor guts, a 3:1 recipient-to-donor ratio was used, with three inocula prepared from each donor gut. To ensure inoculum diversity, at least three different donor guts were always pooled. Thereafter, guts were homogenized and centrifuged (1000 rpm for 30 s). After two days of being exposed to the donor inoculum or being in sterile water, larvae were exposed to the E. coli strain ATCC 11775 or a solvent control for six days. This strain has been shown to reduce growth rate, fat storage and immune defence in damselfly larvae (Janssens and Stoks, 2013). Due to a genetic modification of this strain, by insertion of a dsRed fluorochrome and kanamycin resistant plasmid, pink E. coli colonies can grow on a kanamycin enriched lysogeny broth agar. This allowed straightforward quantification of the bacterial load as pink colonies are shown when plated on a kanamycin enriched lysogeny broth agar. By usage of a spectrophotometer, an initial E. coli concentration of 1 × 10 9 CFU was prepared in sterile Ringer, which was diluted to 8 × 10 7 CFU in sterile dechlorinated tap water. The solvent control consisted of an equal amount of sterile Ringer that was added to sterile dechlorinated tap water. The E. coli concentration did not differ between larvae of both gut microbiome treatments (absence vs. presence), and decreased over the six day exposure period (equalled ca. 8 × 10 7 CFU at day one to ca. 4 × 10 5 CFU at day six, across both gut microbiome treatments). Larvae that were reared until the adult stage, were placed after the initial six days of exposure to E. coli in sterile plastic cups provided with a grid and closed by a net for emergence. Each week, the E. coli medium was renewed for larvae that were reared until the adult stage. Phenotypic response variables The measured larval response variables were mortality (during the initial six days of exposure to E. coli and during the next period until emergence), growth rate, metabolic rate, the critical thermal maximum (CTmax), and the internal bacterial load of the administered E. coli (the E. coli burden: Janssens and Stoks, 2013a). Furthermore, mortality during emergence was quantified as well as mortality in the first day of adulthood, and the CTmax of one day old adults. Both the gut microbiome of larvae (after the initial six days of exposure to E. coli ) and of adults (after one day) was determined. Daily, the survival of larvae and adults was determined to quantify mortality. Since it has been shown that damselfly wet mass strongly correlates with dry mass (Stoks et al., 2005), larval growth rate was determined as the increase in wet mass during the initial six days of exposure to E. coli . First, larvae were gently blotted dry with tissue paper and weighed to the nearest 0.01 mg (using an electronic balance, Mettler Toledo® AB135-S, Ohio, USA). Second, growth rate was quantified as [ln(final mass/initial mass)] divided by six days. After the initial six days of exposure to E. coli , a first set of larvae was used to determine larval metabolic rate, larval CTmax and larval E. coli burden (31 – 34 larvae per treatment combination, total of 131 larvae), a second set of larvae was used to determine the gut microbiome composition (12 larvae per treatment combination, total of 48 larvae), and a third set of larvae was reared until the adult stage. From these adults, a first set of adults was used to determine adult CTmax (23 – 44 adults per treatment combination, total of 138 adults), and a second set of adults was used to determine the abdominal microbiome composition (12 adults per treatment combination, total of 48 adults). The adult internal abdominal-associated microbiome was used as a proxy for the adult gut microbiome because dissection of the gut tract was not feasible due to rapid dehydration and frequent breakage of the gut during dissection (based on own observations). For the determination of the larval metabolic rate, larvae were transferred to sterile glass vials (4 cm height, 1 cm diameter) provided with a small sterile plastic grid (4 cm height, 0.8 cm diameter, 100 µm mesh size) for larvae to sit upon, and filled with sterile dechlorinated tap water (in the absence of food). Oxygen bubbles were prevented by sealing the vials airtight (by providing an excess of sterile dechlorinated tap water on both vial and seal). In a closed respirometry system (Microplate Respirometry, Loligo® Systems, Viborg, Denmark), the decrease in dissolved oxygen (measured every 5 s) was used to estimate the metabolic rate during 45 min at 20 °C (the respirometry system was placed in a water bath). In every trial, a minimum of two control vials were added without a larva but with a grid and sterile water to control for background respiration, and all vials were randomly assigned to a position in the respirometry system. Metabolic rate was expressed as milligram oxygen consumed per hour. After the metabolic rate trials, the CTmax was quantified as a measure of acute heat tolerance. With a dynamic method (Verberk and Bilton, 2013) , during which a constant heating rate is used, the CTmax was determined as the temperature were no body movement or muscular spasms were shown (Verberk and Bilton, 2013) . Larvae were transferred to sterile plastic vials (4 cm height, 2.5 cm diameter) filled with 12 mL sterile dechlorinated tap water (in the absence of food). Vials were randomly placed on the heating block (Digital Block Heater). Initial water temperature equalled 20 °C, and increased at a constant rate of 0.3 °C per minute. This ramping rate is commonly used to assess the CTmax of aquatic insects (Dallas and Rivers-Moore, 2012; Verberk and Bilton, 2013), which is fast enough to avoid acclimation and slow enough to ensure that the body temperature can track the water temperature (Dallas and Rivers-Moore, 2012). When reaching CTmax, larvae were immediately removed from the vials and transferred to their original closed jars at 20 °C for recovery. All larvae recovered within 30 minutes after the CTmax was reached. For the quantification of the E. coli burden, larvae were first washed in absolute ethanol (100 %) after which the head was removed. Larval bodies were homogenized in sterile Ringer solution and the supernatant was used to inoculate culture media in duplicate (Janssens and Stoks, 2013). Two serially diluted assay concentrations were used: 25 µL of a 40 times diluted supernatant, and 10 µL of a 100 times diluted supernatant. After an incubation period of 96 h at 28 °C of the culture media, the number of colonies was counted as a proxy for the E. coli burden, i.e. the mean number of CFU per larva. One day after emergence, adult CTmax was determined (Angilletta et al., 2010), following dynamic method with a ramping rate of 0.3 °C per minute until the CTmax was reached whereby no body movement or muscular spasms were shown (Angilletta et al., 2010). The chosen ramping rate is commonly used to assess the thermal tolerance of terrestrial ectotherms (Terblanche et al., 2011). For this, adults were transferred to sterile plastic vials (6.5 cm height, 5 cm diameter) provided with a sterile plastic grid (6.5 cm height, 3.5 cm diameter) for adults to sit upon (in the absence of food). Vials were randomly placed in an incubator in which the initial temperature equalled 20 °C. When CTmax was reached, adults were immediately transferred to their original plastic cups at 20 °C. Recovery was determined during the first 30 minutes. after CTmax was reached, whereby only 1 out of 139 adults did not recover and subsequently was excluded from the CTmax analyses. Characterization of the microbiome An optimized protocol for the characterization of the gut microbiome of Ischnura damselfly larvae (Theys et al., 2023) was applied and further optimized for Ischnura damselfly adults. DNA was extracted from individual larval gut samples and adult abdominal samples by usage of the NucleoSpin Tissue Kit (Machery Nagel), whereafter the V3-V4 hypervariable region (460 bp) of the 16S rRNA gene was amplified using the 16s-IllumTS-F and 16s-IllumTS-R primers (Klindworth et al., 2013). A Biometra TOne Thermocycler (Westburg) was used to perform the PCR reactions of which the details can be found in Appendix A1 . DNA was quantified with a Quant-iTTM Picogreen kit (Thermo Fisher), whereafter purified amplicons were merged and sequenced (2 × 300) on an Illumina MiSeq platform (KU Leuven Genomics Core) with a MiSeq Reagent Kit v3 (600 cycles). After the Illumina sequencing, the de-multiplexed sequencing reads (FASTQ files, ASCII Phred+33 encoding) were imported and visualized in QIIME2 (version 2022.2; Bolyen et al., 2019), whereafter these paired-end sequences were filtered, denoised (with the “denoised-paired” function of DADA2 within QIIME2 (Callahan et al., 2016)), dereplicated and whereby chimeras were removed. Both in the forward and reverse reads, the first 15 nucleotides were trimmed, whereas forward reads were truncated at 280 base pairs and reverse reads at 240 base pairs. Taxonomy assignment was performed on the amplicon sequence variants (ASVs) table via the Silva 138 SSU Ref NR 99 marker gene reference databases (Klindworth et al., 2013) and a naive Bayesian classifier. Sequences were extracted from the V3-V4 region with the function qiime “feature-classifier extract-reads” and the following parameters: (i) forward primer (341F): 16S-IllumTS: CCTACGGGNGGCWGCAG, (ii) reverse primer (785R): 16S-IllumTS: GACTACHVGGGTATCTAATCC, and (iii) truncation length: 460 base pairs. Afterwards, with the qiime phylogeny “align-to-tree-mafft-fasttree” function, a phylogenetic tree was obtained. With decontam (version 1.10.0; Davis et al., 2018), contaminated DNA features were removed, whereafter the dataset was filtered and cleaned in R (details in Appendix A2 ). With the “rarefy_even_depth” function of the phyloseq package (version 1.38.0; McMurdie and Holmes, 2013), rarefaction was performed at the cut-off level of 9,000 (with 150,150 set as seed parameter for reproducibly random subsampling). Rarefaction resulted in a loss of 58 out of 928 ASVs, the rarefaction curve is presented in Appendix A3 . Statistical analyses Statistical analyses were performed in R version 4.4.0 (R Core Team, 2024). The effects of the re-inoculation and the E. coli treatment, and their interactions were analyzed separately for each phenotypic response variable. For mortality, a bias-reduced generalized linear model with a binomial error distribution and a logit link function was used (“brglm” package, version 0.7.2; Kosmidis, 2022) . For growth rate, metabolic rate, CTmax, the E. coli burden, and time from final instar to emergence, linear models with a normal error distribution and the identity link were used. Larval or adult sex and mass were included as cofactors in all models (except mass was not included in the growth rate model). Larval growth rate was exponentially transformed, larval metabolic rate was boxcox-transformed, and the E. coli burden was (log + 1)-transformed to meet the assumptions of normality and homogeneity of variance of the residuals. For mortality, Wald statistics and associated p-values were used to assess the significance of fixed effects with the ‘stats’ package (R Core Team, 2024) . For the other variables, F-statistics and accompanying p-values of the fixed effects were calculated with the ‘car’ package (version 3.0-12; Fox and Weisberg, 2019). Significant interactions were further examined by pairwise contrasts using FDR-corrected estimated marginal means (“emmeans” package, version 1.7.2; Lenth, 2022). Differences in the gut bacterial species diversity (α-diversity) were investigated by calculating both the observed number of ASVs and the Shannon index with the “estimate_richness” function of the phyloseq package (version 1.38.0; McMurdie and Holmes, 2013), and the Faith’s phylogenetic diversity index with the “pd” function of the picante package (version 1.8.2; Kembel et al., 2010). The effects of the donor and E. coli treatment, and their interactions on both α- and β-diversity metrics were analyzed. For α-diversity, linear models with a normal error distribution and the identity link were used. Further statistical procedures were similar as used for the larval response variables. Effects on the composition of the gut microbial communities (β-diversity) were studied by using permutation MANOVAs with the Bray-Curtis (taxonomic) and Weighted UniFrac (phylogenetic) distance metrics. Models ran with 10,000 permutations using the “adonis2” function of the vegan package in R (version 2.5-7; Oksanen et al., 2020). Multidimensional scaling (MDS) plots were made with the phyloseq package in R (version 1.38.0; McMurdie and Holmes, 2013). Results Response patterns in the host’s phenotype During the first six days of exposure, mortality was the lowest for larvae that received a donor gut microbiome (after depletion of the gut microbiome) without being exposed to E. coli , and increased (ca. 42 %) when larvae did not receive a donor gut microbiome regardless of the E. coli treatment, or when they did receive a donor gut microbiome but were exposed to E. coli (contrasts: all P < 0.047; Table 1, Fig. 1A ). Larval growth rate, metabolic rate, E. coli burden, and CTmax were not affected by either the donor gut microbiome or the E. coli treatment ( Table 1, Fig. 1B-E ). Female larvae showed a lower mortality and tended to have a higher CTmax than male larvae ( Table 1 ). After the first six days of exposure, larval mortality, mortality during emergence, time from final instar to emergence, and adult CTmax were not affected by either the donor gut microbiome or the E. coli treatment ( Table 2, Fig. 2A, B, D & E ). However, adult mortality during the first 24h after emergence tended to increase (ca. 20 %) when exposed to E. coli during the larval stage, independent of the donor gut microbiome treatment ( Table 2, Fig. 2C ). Response patterns in the gut microbiome The microbiome of larval and adult damselflies consisted of the phyla Bacteroidota (15.22 %), Actinobacteriota (1.05 %), Planctomycetota (0.30 %), Verrucomicrobiota (0.20 %), and was dominated by the phylum Proteobacteria (83.14 %) of which the most abundant families were Anaplasmataceae (30.62 %), Xanthomonadaceae (22.17 %), Flavobacteriaceae (9.39 %), Comamonadaceae (9.21 %), and Pseudomonadaceae (7.21 %; Fig. 3 ). Adults showed a more diverse microbiome than larvae for the three species diversity indices (contrasts: all P < 0.001, Table 3, Fig. 4 ). Furthermore, larvae that received a donor gut microbiome showed a higher number of observed ASVs compared to larvae that did not (contrast: P = 0.004, Table 3, Fig. 4A ). In contrast, no difference in number of observed ASVs was found in adults, regardless whether they had received a donor gut microbiome during the larval stage or not (contrast: P = 0.546, Table 3, Fig. 4A ). The bacterial community composition differed between larvae and adults across both diversity metrics ( Table 3, Fig. 5 ). The larval microbiome comprised 295 ASVs and the adult microbiome 316 ASVs, with 82 ASVs shared between life stages. These shared ASVs belonged to the phyla Proteobacteria (50 ASVs), Bacteroidota (24 ASVs), Actinobacteriota (5 ASVs), Planctomycetota (2 ASVs), and Armatimonadota (1 ASV; Appendix A4, Table A4.1 ). When comparing between life stages, a higher abundance of 12 ASVs was found for the larval microbiome, and 41 ASVs for the adult microbiome ( Appendix A4, Table A4.2 ). Using the Unweighted UniFrac metric, which considers phylogenetic distances, E. coli exposure was found to impact the community composition ( Table 3, Fig. 5B ), whereby exposure to E. coli increased the abundance of 3 ASVs, which belonged to the genera Escherichia-Shigella (1 ASV) and Pseudomonas (2 ASVs; Appendix A4, Table A4.3 ). Additionally, there was a trend for an interaction between the donor gut microbiome treatment and life stage, which indicated that the microbial community composition differed between donor treatments in larvae (contrast: P < 0.001), but not in adults (contrast: P = 0.107, Table 3, Fig. 5B ). Overall, 145 ASVs were detected in the microbiome of larvae that did not receive a donor gut microbiome, and 207 ASVs in those that did, of which two ASVs from the genus Pseudoxanthomonas had a higher abundance in larvae that did receive a donor gut microbiome ( Appendix A4, Table A4.4 ). Discussion Ontogenetic shifts and retention of microbiome composition across metamorphosis The microbiome community composition differed between the larval and adult life stages, a pattern observed before in species occupying different habitats during different life stages (e.g., beetles: Arias-Cordero et al., 2012; frogs: Knutie et al., 2017; insects in general: Manthey et al., 2022; dragonflies: Nobles & Jackson, 2020; mosquitoes: Wang et al., 2011). The basis for this divergence has been attributed to the ecological shift from the aquatic to the terrestrial environment with different abiotic (e.g., temperature, nutrient levels) and biotic (e.g., food resources, developmental changes) factors (Chen et al., 2017; Nobles and Jackson, 2020). Furthermore, adults showed a higher microbiome diversity than larvae, which has been found before in holo- and hemimetabolous insects, including bugs ( Graphosoma lineatum ), bees ( Osmia bicornis and O. cornuta ), beetles ( Leptinotarsa decemlineata ), butterflies ( Aglais io ), and flies ( Drosophila melanogaster ) (Manthey et al., 2022). However, this finding contrasts with expectations based on the disruptive effect of metamorphosis, which is typically associated with a reduction in microbiome diversity (Johnston and Rolff, 2015), followed by reassembly from exposure to new food resources (Hammer et al., 2014). In current study, adults were only kept for 24 hours post-metamorphosis without access to a food resource, which thus limited the potential to increase microbiome diversity. Despite the differences in microbiome diversity and community composition, adults shared 82 ASVs with larvae (of the total number 295 ASVs in larvae and 316 ASVs in adults), demonstrating partial retention of the larval microbiome across metamorphosis. This aligns with research on dragonflies, where certain bacterial strains persisted across metamorphosis, indicating that complete microbiome turnover during metamorphosis does not necessarily occur in damselflies and dragonflies (Nobles and Jackson, 2020), as also documented in other hemimetabolous aquatic insects (Manthey et al., 2022; Yun et al., 2014). Moreover, differences in the timing of microbiome sampling relative to antibiotic treatment likely contributed to the observed patterns. Larval gut microbiomes were sampled only six days after the antibiotic treatment, whereas individuals sampled as adults had on average more than 50 days to reassemble their microbiome upon sampling. Notably, adult microbiomes also harboured ASVs that were not detected in larval microbiomes, which may suggest additional colonization during or after metamorphosis. Yet, differences in the sampled tissues may also have played a role. Because gut dissections in adults were not feasible (see Materials and Methods), the internal abdominal microbiome was used as a proxy, and thus may have included microbes from the haemolymph or other internal tissues, other than the gut. Survival cost of microbiome disruption and subsequent recovery by inoculation When the gut microbiome of damselfly larvae was strongly reduced by antibiotic exposure, which has been shown to remove 99 % of the resident gut bacteria of damselfly larvae (Theys et al., 2025), mortality increased by ca. 42 % in larvae that did not receive a donor gut microbiome after microbiome disruption. Since the gut microbiome is known to influence host fitness by affecting life history, behaviour, and physiological traits (Gupta and Nair, 2020; Lynch and Hsiao, 2019; Macke et al., 2017) its depletion likely disrupted beneficial functions, potentially contributing to the observed increase in mortality. Importantly, when larvae received a donor gut microbiome after microbiome depletion, their fitness was restored, which aligns with results found in other taxa (Peerakietkhajorn et al., 2015; Salem et al., 2013; Sison-Mangus et al., 2015; Tang et al., 2023; Tian et al., 2023). The restored fitness after re-inoculation indicates that the observed adverse effects were due to the strong reduction of the gut microbiome rather than direct effects of the antibiotic treatment. This is further supported by a study which optimized the antibiotic protocol and demonstrated that the treatment itself does not affect the fitness of damselfly larvae (Theys et al., 2025). The experimental evidence presented in current study demonstrates that damselflies rely on a gut microbiome, which contrasts with the suggestion by Hammer et al. (2019) that dragonflies, the other suborder of Odonata next to damselflies, do not require a microbiome as they harboured only few or no resident microbes. Although the donor inoculum contained a high number of observed ASVs (50 ASVs), larvae that received a donor gut microbiome showed a lower number of observed ASVs compared to the donor inoculum (26 vs. 50 ASVs, respectively), but more ASVs than the larvae that did not receive an inoculum (26 vs. 18 ASVs, respectively), suggesting only a subset of the ASVs present in the donor inoculum to be successfully established. Furthermore, the gut microbiome community composition was different between larvae that received a donor gut microbiome compared to those that did not, whereby the latter had a higher relative abundance of the genus Pseudoxanthomonas . This genus is part of the family Xanthomonadaceae that has previously been associated with reduced larval growth rates in damselflies (Theys et al., 2023). Although no such effect was observed in current study, it is possible that this genus may have contributed to the higher mortality observed in larvae that did not receive a donor gut microbiome. However, as gut microbiomes could not be sampled from deceased individuals, this remains speculative. It is important to note that the larvae were not maintained under sterile conditions after the antibiotic treatment. Although the medium was refreshed weekly with sterile water and the larvae were given sterile Artemia nauplii, the larvae could still acquire environmental microbes (e.g., airborne microbes), mimicking a realistic post-antibiotic recovery scenario. The intention was to transiently reduce the gut microbiome, comparable to a single antibiotic exposure event, while allowing reassembly from environmental sources or through experimental gut microbiome re-inoculation (i.e., by inoculation with a donor gut microbiome). The observed increase in mortality among larvae that did not receive a donor gut microbiome suggests that spontaneous recolonization from environmental sources alone was insufficient to restore a functional gut microbiome in time, supporting the idea that the microbiome can critically affect host survival (Gupta and Nair, 2020; Lynch and Hsiao, 2019; Macke et al., 2017; Peerakietkhajorn et al., 2015). In contrast, larvae that survived did not show further fitness reductions, indicating that once a functional microbiome was re-established, either naturally or via donor gut microbiome inoculation, host fitness could recover. This highlights the importance of timely and effective microbiome reassembly in mitigating the negative effects of microbiome disruption. Furthermore, the increased mortality of not receiving a donor gut microbiome was only seen in the larval stage, and not in the adult stage, meaning that no microbiome-mediated carry-over effects on damselfly adults were found. Moreover, the differences in microbiome diversity and community composition were no longer apparent in adults, where microbiome diversity increased, and community composition merged, regardless of the donor gut microbiome treatment. This convergence suggests that recolonization from the environment over time, after an initial reduction in gut microbiota, may have played an important role in shaping both the larval and adult microbiome, as seen in other species (Carlson et al., 2017; Cooper et al., 2022; Ma et al., 2019; Palleja et al., 2018; Ruan et al., 2024). The absence of differences in other α-diversity metrics, regardless of whether larvae were re-inoculated with a donor gut microbiome, further indicates that the microbial species diversity was re-established relatively quickly in surviving larvae. Consequently, this capacity for rapid recovery in species diversity and potentially also functionality of the gut microbiome may explain why no adverse fitness effects were found on growth rate, metabolic rate and CTmax of larvae that did not receive a donor gut microbiome. Pathogen exposure increases mortality across life stages Exposure to E. coli increased larval mortality, yet this only tended to be the case for larvae that received a donor gut microbiome. Furthermore, the continuous E. coli exposure during the larval stage tended to result in a higher mortality in the adult stage, suggesting that although the adults were not directly exposed to E. coli , the pathogenic effects carried over to the adult stage. Carry-over effects of larval stressors to the adult stage have been documented in multiple semi-aquatic organisms (Stoks et al., 2022b), including damselflies (De Block and Stoks, 2005). Whether or not larvae received a donor gut microbiome, the larval E. coli burden did not differ. Potentially, since E. coli is known to be a strong competitor in animal intestines (Kaper et al., 2004; Taj et al., 2014), it may have outcompeted resident gut microbiota, allowing it to proliferate even in hosts with an intact gut microbiome. This was supported by the observed shift in community composition following E. coli exposure, whereby the relative abundance of the genus Escherichia-Shigella increased in both life stages, independent of the donor gut microbiome treatment. While species-level identification was not possible due to limitations of 16S rRNA gene sequencing, the increase likely reflects the introduced E. coli strain, as Escherichia and Shigella are closely related and often indistinguishable using this marker (Chattaway et al., 2017). Although members of the genera Escherichia-Shigella are sometimes commensal, they can act as opportunistic pathogens, particularly in immunocompromised hosts (Braz et al., 2020; The et al., 2016). Thus, the E. coli -induced mortality found in both life stages confirms that the pathogen can negatively impact the fitness of aquatic organisms, as found in zebrafish, mosquitoes, water fleas, and damselflies (Barber et al., 2016; Brown et al., 2018; Goncharuk and Vergolyas, 2014; Janssens and Stoks, 2014, 2013; López Lastra et al., 2004). Moreover, the genus Pseudomonas also had a higher relative abundance in the microbiome of both life stages after larval exposure to E. coli . This genus is known for some beneficial functions, such as facilitation of nutrition and defence, thereby increasing insect survival (Bozorov et al., 2019; Ceja-Navarro et al., 2015; Gupta et al., 2022; Kellner, 2003; Piel et al., 2004). However, some Pseudomonas strains are known to have detrimental impacts, even causing an increased mortality by production of toxic secondary metabolites and thereby killing invertebrates such as D. magna and other aquatic species (Martin-Creuzburg et al., 2011; Sinden et al., 1971; Tan et al., 1999). Given their dual role as potential mutualists and pathogens, changes in Pseudomonas abundance could have important consequences for host physiology and fitness, especially under stress. Furthermore, another potential explanation could be that E. coli exposure reduced the damselflies energy reserves, mainly the fat content (Janssens and Stoks, 2013). This could have resulted in energy-mediated trade-offs, whereby mounting an immune response to pathogens such as E. coli can divert energy away from other vital functions, potentially contributing to the observed increase in mortality (Schmid-Hempel, 2005). Survival selection may explain the lack of negative effects beyond mortality Since both larval and adult mortality were higher due to the strong reduction of the gut microbiome without following inoculation with a donor gut microbiome and/or E. coli exposure, survival selection may explain the absence of effects on other traits than mortality. Survival selection is a process whereby only individuals with certain traits, typically those conferring greater robustness or stress tolerance, survive under challenging conditions. As a result, trait measurements are potentially performed on a biased subset of survivors that are less sensitive to microbiome disruption without inoculation and/or pathogen exposure, which could have masked treatment effects on sublethal traits such as growth rate. Intriguingly, while the trend for an increased adult mortality following larval exposure to E. coli suggests a negative impact on overall fitness, no adverse effects were observed in the measured larval traits, other than mortality. Potentially, the continuous exposure to E. coli during the larval stage imposed substantial energetic costs on traits in larvae and adults that were not measured in current study such as morphology (e.g., wing malformations and flight muscle reductions (Dinh et al., 2016a, 2016b)), physiology (e.g., reduced fat content and immune functioning (Debecker et al., 2015; Stoks et al., 2006b)), gene expression (e.g., mRNA expression related to proteins production and expression of immune enzymes (Boone et al., 2013; Xie et al., 2015)) or epigenetic mechanisms (e.g., DNA methylation (Metzger and Schulte, 2018)). Furthermore, a common consequence of stressor exposure in the larval stage is a decrease in successful metamorphosis (Stoks et al., 2022a). Yet, in current study, larvae may have retained enough energy to successfully complete metamorphosis, which likely came at the cost of post-metamorphic energy reserves, ultimately leading to a trend for an increased mortality in the adult stage. Conclusions A central challenge in life-history theory is to determine how stressors experienced during early life stages can shape fitness in later life stages. Especially in animals with complex life cycles, stress experienced during larval development can lead to negative carry-over effects across metamorphosis, affecting performance in the adult life stage (Moore and Martin, 2019; Rolff et al., 2019) . While such effects are increasingly recognized, the mechanisms mediating them remain poorly understood. One potential mediator is the host-associated microbiome which is increasingly recognized as key contributor to host fitness (Gupta and Nair, 2020; Lynch and Hsiao, 2019; Macke et al., 2017; Peerakietkhajorn et al., 2015). However, its role in mediating stressor effects, especially across metamorphosis, remains poorly understood . This is particularly relevant in animals with complex life cycles involving metamorphosis, (González-Serrano et al., 2020; Moll et al., 2001) , whereby stressors might directly or indirectly alter microbiome diversity and community composition (Bénard et al., 2020; de Muinck et al., 2013; Dillon and Dillon, 2004; Hartman and Tringe, 2019; Monnin et al., 2016; Williams et al., 2016) potentially leading to negative fitness effects. Current study reveals that microbiome disruption via an antibiotic treatment significantly increased larval mortality, whereby this adverse effect was mitigated by inoculation with a donor gut microbiome. This underscores the microbiome’s functional importance in damselflies, thereby emphasizing its critical role determining host fitness. Moreover, pathogen exposure not only elevated larval mortality but also tended to induce delayed mortality effects in the adult stage, highlighting the potential for carry-over effects from aquatic larval to terrestrial adult environments. Despite marked shifts in microbiome composition across metamorphosis, partial retention of larval microbial taxa suggests continuity in microbial associations across life stages, supporting the emerging insight that metamorphosis in hemimetabolous insects does not entail a complete microbiome turnover (Manthey et al., 2022; Nobles and Jackson, 2020; Yun et al., 2014). Furthermore, despite the strong initial effects of microbiome disruption, no microbiome-mediated carry-over effects on damselfly adults were found, potentially due to survival selection or compensatory recovery of the microbiome over time. 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Effect z 1,724 P F 1,627 P F 1,122 P F 1,47 P F 1,107 P Donor 3.501 <0.001 1.722 0.190 0.824 0.366 0.133 0.716 0.193 0.662 E. coli -2.280 0.023 2.222 0.137 0.137 0.712 0.495 0.483 / / Sex -3.322 0.001 1.300 0.255 0.068 0.795 3.706 0.057 0.300 0.586 Mass / / / / 0.293 0.589 0.030 0.864 0.145 0.705 Donor * E. coli 1.668 0.095 0.191 0.662 0.043 0.836 0.133 0.716 0.193 0.662 Table 2 Results of linear models testing for effects of the donor gut microbiome (Donor) and E. coli exposure ( E. coli ) on mortality (after the first 6 days of exposure to E. coli , mortality during emergence, mortality of adults, time from F0 to emergence, and adult CTmax of Ischnura elegans damselfly larvae and adults. Significant P-values (< 0.05) are given in bold, P-values that indicate a trend (< 0.10) are in italics. Effect z 1,645 P z 1,566 P z 1,230 P F 1,131 P F 1,131 P Donor 0.109 0.913 0.346 0.730 -0.231 0.817 0.171 0.679 0.049 0.826 E. coli -0.244 0.807 0.101 0.920 -1.670 0.095 1.184 0.278 0.441 0.508 Sex -0.979 0.328 -0.859 0.390 -0.885 0.376 0.065 0.799 0.005 0.942 Mass / / / / / / 6.705 0.010 0.406 0.525 Donor * E. coli 0.218 0.828 -0.598 0.550 -0.346 0.730 1.940 0.165 0.696 0.406 Figure 1 Patterns in (A) mortality (during the first 6 days of exposure to E. coli ), (B) growth rate, (C) metabolic rate, (D) CTmax and (E) the E. coli burden of I. elegans damselfly larvae as a function of the donor gut microbiome and E. coli exposure . Given are means ±1 SE. Different letters denote significantly different means based on pairwise contrasts. Figure 2 Patterns in (A) mortality (after the first 6 days of exposure to E. coli , (B) mortality during emergence, (C) mortality of adults, (D) time from F0 to emergence, and (E) adult CTmax of Ischnura elegans damselfly larvae and adults as a function of the donor gut microbiome and E. coli exposure . Given are means ±1 SE. Figure 3 Relative abundance (%) of bacterial families in the gut microbiome of Ischnura elegans damselfly larvae and adults as a function of the donor microbiome (Donor) and E. coli treatment ( E. coli ). Colours indicate different bacterial families. Families with an occurrence of <1 % are represented as ‘Rare families’. Table 3 Results of linear models and of PERMANOVA testing for effects of the donor microbiome (Donor) and E. coli treatment ( E. coli ) on the α-diversity and the β-diversity metrics of the gut and abdominal microbiome of Ischnura elegans damselfly larvae and adults ( Life stage) , respectively. Significant P-values (< 0.05) are given in bold, P-values that indicate a trend (≤ 0.10) are in italics. Observed number of ASVs Shannon index Faith’s phylogenetic diversity Bray-Curtis Unweighted UniFrac Effect F 1,86 P F 1,86 P F 1,86 P F 1,86 P F 1,86 P Donor 6.619 0.012 1.492 0.225 2.214 0.141 1.199 0.269 2.228 0.052 E. coli 1.076 0.303 0.177 0.675 0.692 0.408 1.289 0.219 3.397 0.011 Life stage 67.240 <0.001 16.489 <0.001 72.755 <0.001 12.458 <0.001 46.177 <0.001 Sex 0.002 0.964 1.438 0.234 0.174 0.678 1.548 0.132 1.121 0.275 Donor microbiome * E. coli 0.321 0.572 0.201 0.655 0.116 0.735 1.122 0.310 1.319 0.194 Donor microbiome * Life stage 2.957 0.089 0.161 0.689 0.260 0.611 1.639 0.109 2.009 0.070 E. coli exposure * Life stage 0.007 0.933 0.347 0.558 0.834 0.364 1.414 0.171 1.261 0.214 Donor * E. coli * Life stage 0.002 0.964 0.004 0.950 0.058 0.810 0.820 0.561 1.188 0.235 Figure 4 Effects of the donor microbiome (Donor) and E. coli treatment ( E. coli ) on the α-diversity of the gut and abdominal microbiome of Ischnura elegans damselfly larvae and adults, respectively : (A) Observed number of ASVs, (B) Shannon index, and (C) Faith’s phylogenetic diversity. Means are given ±1 SE. Figure 5 Non-metric multidimensional scaling (NMDS) plot representing the Bray-Curtis (A) and the Unweighted UniFrac (B) dissimilarities in gut microbiome composition in response to the donor microbiome (Donor) and E. coli treatment ( E. coli ) of Ischnura elegans damselfly larvae and adults, respectively. Shown are MDS1 vs. MDS2 axes; treatment means are given with 95% CI. Information & Authors Information Version history V1 Version 1 04 August 2025 Copyright This work is licensed under a Non Exclusive No Reuse License. Keywords aquatic invertebrates life stages microbiome reduction microbiota pathogen tolerance transplant Authors Affiliations Charlotte Theys 0000-0002-8247-3228 [email protected] KU Leuven View all articles by this author Julie Verheyen KU Leuven View all articles by this author Alessio Cocco 0000-0002-7932-8687 KU Leuven View all articles by this author Ellen Decaestecker KU Leuven - Kulak Kortrijk Campus View all articles by this author Robby Stoks KU Leuven View all articles by this author Metrics & Citations Metrics Article Usage 217 views 155 downloads .FvxKWukQNSOunydq8rnd { width: 100px; } Citations Download citation Charlotte Theys, Julie Verheyen, Alessio Cocco, et al. Strong microbiome disruption reduces damselfly survival, and subsequent pathogen exposure tends to increase mortality across metamorphosis. Authorea . 04 August 2025. 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