Introduction

Interactions between bacteria and fungi in various habitats are important for the functioning of biological systems [1]. It is well known that in vertebrate animals, these interactions may be modulated by different factors, including infectious diseases and toxicant stresses [2]. However, these effects have been insufficiently studied in invertebrates. Insect bacterial communities are known to play an important role in different aspects of the host’s life, from beneficial to detrimental, and their nature can be shifted depending on biotic and abiotic factors. The most important beneficial functions include the promotion of digestion, host metabolism regulation, the detoxification of plant allelochemicals, the stimulation of growth and development, and the induction of immune response protection from pathogenic microorganisms [3, 4]. In addition to these beneficial properties, the insect gut microbiota may be harmful to their hosts under certain conditions [5]. Alterations in the bacterial community structure may modulate host susceptibility to fungal [6] and bacterial pathogens [7]. It is also known that symbiotic bacteria participate in response to toxicoses caused by chemical insecticides [8, 9], and the microbiome structure of insects may be changed significantly under the influence of insecticides [10]. Importantly, insects are exposed to various toxicants and pathogens during their development, which can lead to complex effects on the host’s microbiota that will ultimately affect their survival.

Interactions between symbiotic insect bacteria and pathogens include (i) suppression or competitive exclusion [11, 12], (ii) the stimulation of the host’s immune system [13], (iii) the production of antimicrobial compounds [14, 15], and (iiii) synergy between symbiotic and pathogenic microorganisms [6, 16, 17]. The influence of the microbial community on the development of mycoses may be different depending on the insect and fungal species and on environmental factors. The mortality rate of axenic insects infected with entomopathogenic fungi was shown to be significantly higher [18, 19] or significantly lower [6, 16] compared with non-axenic insects. It is likely that antagonistic or synergistic effects between fungi and bacteria depend on the type of fungal infection. With oral administration, a direct interaction between the fungi and gut bacteria occurs, which leads primarily to an antagonistic effect since many gut bacteria inhibit fungal growth and differentiation of infection structures [11, 15, 19, 20]. Topical fungal infections lead to more complicated interactions through the host’s immunity as well as through direct interactions between microorganisms and their metabolites. They can cause both types of interactions between fungi and bacteria, antagonistic [18] and synergistic [6, 16, 17]. Despite the possible presence of antagonistic symbionts in insects, the antifungal effect may be absent for a number of reasons, such as (i) a low relative abundance of these bacteria, (ii) interactions with other organisms, (iii) the influence of other environmental factors, and/or (iiii) the production of antibacterial compounds by the fungi [21].

Blood-sucking mosquitoes are an important component of aquatic ecosystems. Many species, and in particular Aedes aegypti, play a significant role as a vector of serious human diseases. In the past few decades, entomopathogenic ascomycetes have often been used as an alternative to chemical insecticides for mosquito control. Among them, entomopathogenic fungi from the Metarhizium and Beauveria genera are actively being developed for use against mosquito larvae and adults [22, 23]. The effectiveness of Metarhizium conidia and blastospores in the biocontrol of Ae. aegypti larvae and adults has been recently reviewed by Aw and Hue [23].

The influence of mycoses on the microbiota of mosquito was explored in study by Frankel-Bricker and coworkers [24], who showed that the fungal colonization of Ae. aegypti larvae by the trichomycete Zancudomyces culisetae reduced the microbial community variation across individuals and influenced on adult microbiomes. The effects of topical infections by the ascomycetes Beauveria and Isaria on the microbiota of mosquito adults has been studied in detail in Anopheles and Aedes species [6, 25]. Wei and coworkers [6] demonstrated that topical infections of Anopheles stephensi with Beauveria bassiana lead to the increased proliferation of Serratia in the gut followed by bacterial penetration into the hemocoel, which accelerates the host’s death from mycosis. Ramirez and coauthors [25] also demonstrated an increase in the total bacterial load in the gut of Ae. aegypti adults after Beauveria and Isaria infection; however, no changes in the bacterial community structure were registered. The abovementioned authors explained these changes based on the prioritization of the immune response between the cuticle and the gut, as well as by the action of fungal secondary metabolites. It is important to note that in mosquito larvae, unlike adults, fungal infections of Metarhizium develop in a completely different way, through the accumulation of fungal conidia in the gut [26] or fungal growth in the siphon with subsequent suffocation [27]. In Ae. aegypti larvae, Metarhizium conidia are unable to adhere to the body surface, including the siphon, and the primary organ of conidia accumulation is the gut [26, 28]. The reason for the subsequent death of Ae. aegypti larvae may be protease-induced stress without the differentiation of infectious structures [26] or the colonization of the hemocoel by the fungus [29, 30]. Because the gut is the major reservoir of bacteria in insects, the fungus interacts directly with the bacteria in the mosquito larvae under this type of pathogenesis. It is possible that these bacteria may exhibit fungistatic properties, or, alternatively, they may act as synergists of the fungi.

Because insecticides can lead to shifts in the bacterial community within insects, it is reasonable to expect a change in their susceptibility to fungi. However, there are no data on the combined effects of entomopathogenic fungi and insecticides on the microbiota of mosquito larvae. Previously, we showed a synergistic effect between the entomopathogenic fungus Metarhizium robertsii and the neurotoxic insecticide avermectin in the mortality of Ae. aegypti larvae [30]. We suggested that this synergistic effect occurs because of the disturbance of the detoxifying and immune responses at the initial stage of toxicosis and mycosis. We also showed that the fungus was able to colonize the hemocoel in larvae and to form external sporulation. We registered a decrease in the antibacterial activity and an increase in the CFUs of cultivable bacteria from mosquito larvae under the influence of these agents, and thus we hypothesized that the synergistic effect can be mediated by changes in the bacterial community.

In this study, we examined the changes in the bacterial community structure of Ae. aegypti larvae under the influence of M. robertsii and avermectins. In addition, we identified cultivable bacteria from the predominant taxa and investigated the relationships of these bacteria with the fungus in vitro and in vivo. This study shows the impact from the bacterial associates of Ae. aegypti larvae during fungal pathogenesis.

Materials and Methods

Mosquito, Fungus and Insecticide

Ae. aegypti larvae from the collection at the Institute of Systematics and Ecology of Animals SB RAS (Novosibirsk, Russia) were reared under controlled laboratory conditions in settled tap water (24 ± 1 °C, 30 ± 10% RH, 12:12 L/D photoperiod). The larvae were fed daily with Tetramin Junior fish food (Tetra, Germany). The adults were fed with 10% sugar solution ad libitum and given blood meal by feeding on a human hand. The adult female mosquitoes laid their eggs on wet filter paper or in a Petri dish containing settled tap water. The hatched larvae were transferred to a glass container containing 1 L of settled tap water and fed daily. Fourth-instar larvae were used in the experiments, as this age is the longest. This precludes the influence of molting on pathogenesis.

The conidia from the MB-1 strain of Metarhizium robertsii from the institute’s collection were grown on autoclaved millet for 10 days at 26 °C in the dark, followed by drying and sifting, and then stored at 4 °C. The industrial product “Phytoverm” 0.2% (SPC “Pharmbiomed”, Russia) was used in the experiments as a chemical insecticide. This product includes a complex of natural avermectins (A1a (9%), A2a (18%), B1a (46%), and B2a (27%)) that are produced by Streptomyces avermitilis.

Treatment Procedures and Colonization Assessment

The treatments were conducted using 200-mL plastic containers containing 100 mL of settled tap water with 15 fourth-instar larvae. The experiment included four treatments, that is, the control, fungus, avermectins, and fungus + avermectins (combined treatment). Both the fungal conidia and avermectins were suspended in distilled water, vortexed, and applied separately or in combination at equal volume (1 mL per container). The final concentrations were 6 μg/L for avermectins (active substance) and 106 conidia/mL for the fungus. The same amount of distilled water was added to the control treatment. The mortality assay was performed using at least 6 replicates for each of the treatments (one replicate included 15 larvae). The mortality data were recorded daily for 6 days.

The fungal colonization of the mosquitoes was assessed from the 3rd to 6th days posttreatment. Newly dead larvae were squeezed onto a glass slide and the contents were observed for the presence of fungal hyphal bodies using light microscopy (Total—n = 52 for the fungus and fungus + avermectins treatments). To visualize the fungal structures, the mosquito larvae (2–3 days posttreatment) were fixed in a 0.2% solution of glutaraldehyde and 0.1 M Na-cacodylate buffer (pH 7.2). The sample preparation for making ultrathin sections included washing with cacodylate buffer followed by postfixation in 1% (w/v) OsO4 in the cacodylate buffer. The samples were then dehydrated in an ethanol series, placed in an Epon-Araldite 812 mixture, and sectioned with a Reichert Ultracut S ultramicrotome (Leica, Nussloch, Germany). The ultrathin sections were stained with lead uranyl acetate and lead citrate and viewed on a Hitachi-300 or JEM-100CX electron microscope.

DNA Extraction and Illumina Sequencing

Forty-eight hours posttreatment, the mosquito larvae were dipped in 0.5% chlorhexidine for 10 s, washed in sterile water, and frozen in liquid nitrogen. Four biological replicates (one replicate = 10 larvae) from each treatment were used for the analysis. The total DNA was extracted using a DNeasy PowerSoil Kit (Qiagen). Bead beating was performed using TissueLyser II (Qiagen) for 10 min at 30 Hz.

The V3-V4 region of the 16S rRNA genes was amplified with the 343F and 806R primer pair combined with Illumina adapter sequences as described previously [31]. A total of 200 ng of PCR product from each sample (a mix of three technical replicates) was pooled together and purified with a MinElute Gel Extraction Kit (Qiagen). The 16S libraries were sequenced with 2 × 300-bp paired-ends reagents on MiSeq (Illumina) in the SB RAS Genomics Core Facility (Institute of Chemical Biology and Fundamental Medicine SB RAS, Novosibirsk, Russia).

The raw sequences were analyzed using the UPARSE pipeline [32] with Usearch v11.0.667. The UPARSE pipeline included the merging of paired reads, read quality filtering, length trimming, merging of identical reads (dereplication), discarding of singleton reads, removal of chimeras, and OTU clustering using the UNOISE algorithm [33]. The alpha diversity metrics were also calculated in Usearch. Rarefaction and extrapolated curves were generated using the “iNEXT” package [34]. The final data set contained 215 OTUs and 446.856 reads (27.929 ± 1.800 reads per sample, see Appendix A). All the rarefaction curves followed a trend of approaching the saturation plateau, which indicated a reasonable volume of reads (Appendix B, Fig. S1). The raw MiSeq reads were deposited in GenBank under project accession number PRJNA625381.

Bacterial Load Determination by qPCR

The larvae were collected at 48 h posttreatment. Sample preparation was performed as described in the previous section. The total bacterial 16S rRNA was determined in relation to the mosquito reference genes as described by Ramirez et al. (2018). Ten larvae were pooled in one sample. The RNA was extracted with QIAzol® Reagent (Qiagen) for DNA, RNA, and protein isolation according to the manufacturer’s instructions. The RNA concentration and purity were detected spectrophotometrically. DNase treatment was performed with RQ1 RNase-free DNase (Promega). The RNA was converted to cDNA using 6 mg of DNA-free RNA, 2 μL of 100 nM random nanomers, and 1 μL of RevertedAidTM M-MuLV Reverse Transcriptase (Fermentas, Lithuania).

qPCR was performed in three technical replicates under the following conditions: 95 °C for 3 min; followed by 40 cycles of 94 °C for 15 s and annealing and elongation at 62 °C for 30 s; and then melting curves were generated (70–90 °C). The qPCR was developed with HS-qPCR SYBR Blue (2×) mix (BioLabMix, Russia) by CFX96 Touch (Bio-Rad). Two genes from Ae. aegypti were used as reference genes, namely, the 60S ribosomal protein L32 (Rp49) and 40S ribosomal protein S17 (Rps17). To detect the total bacterial cDNA, universal primers for 16S were used. The primer sequences are shown in Appendix B (Table S1). The primer properties were tested using IDT OligoAnalyzer 3.1 (http://eu.idtdna.com/calc/analyzer). Seven replicates per treatment were used for the analysis.

CFU Counts and Identification of Cultivable Bacteria

The larvae were collected at 48 h posttreatment. The sample preparation was conducted as described in the previous sections, but the insects were not frozen. The larvae were homogenized in 1 mL of cooled, sterile 150 mM sodium chloride (1 sample = 3 larvae). One hundred microliters of the suspensions in 10−1, 10−2, 10−3, and 10−4 dilutions were inoculated in 90-mm Petri dishes containing Blood agar ™, Aeromonas medium ™, Endo agar ™ (Himedia Lab., India) and Flavobacteria medium. The Flavobacteria medium was composed of (g/L) 5—tryptose, 5—trehalose, 2—yeast extract, 3—sodium chloride, 0.2—magnesium sulfate, 0.2—Iron (III) chloride, 0.1—bromothymol blue, and 15—agar. Colony counting was performed after 72 h of incubation at 28 °C. Morphologically different colonies were isolated into pure cultures after three passages.

The putative species were determined by sequencing the 16S rRNA gene sequences and comparing them with those available in the NCBI GenBank Database (www.ncbi.nlm.nih.gov/genbank). Bacterial suspensions prepared from the individual colonies were boiled and lysates were used as a template to amplify the 16S rRNA gene. PCR was performed using the primers 16S-8-f-b 5 ′-AGRGTTGATCCCGGCTCA-3′ and 16S-1350-r-B 5 ′-ACGGCGGGTGTGTACAANG, and it resulted in 1342-bp DNA fragments. The sequencing of the resulting PCR fragments was performed using the same primers and a Terminator v.3.1 BigDyeTM kit (Applied Biosystems, USA) according to the manufacturer’s protocols. Capillary electrophoresis was performed on ABI 3500 Genetic Analyzer (Applied Biosystems, USA). The nucleotide sequences were verified using Sequencher v.4.0.5. The closest bacterial sequences from the GenBank Database (at a sequence similarity level of at least 98%) were used to determine the putative species. Twenty-four sequences were deposited in the GenBank Database (MT040033–MT040056).

Antagonistic Effects of the Cultivable Bacteria Towards Fungus In Vitro

The bacteria Chryseobacterium cucumeris, Microbacterium paraoxydans, Delftia sp., and Pseudomonas putida were isolated from the laboratory lines of Ae. aegypti. The bacteria Aeromonas hydrophila (СEMTC 2088) were obtained from a collection of extremophilic microorganisms and type cultures at the Institute of Chemical Biology and Fundamental Medicine SB RAS (Novosibirsk, Russia); together, they were analyzed for antagonistic activity. The plugs of 1-day-old bacterial cultures (Nutrient agar ™; Himedia Lab., India) were placed on a freshly plated culture of M. robertsii in 90-mm Petri dishes with Sabouraud dextrose agar. The Petri dishes were incubated at 28 °C in the dark. The inhibition zone of mycelial growth (mm) was evaluated after 144 h of incubation. At least 4 replicates were used in the assay.

Combined Effects of Bacteria and M. robertsii on Mosquito Larvae

The bacteria C. cucumeris, M. paraoxydans, A. hydrophila, Delftia sp., and P. putida were cultivated on Nutrient agar™ (Himedia). One-day-old colonies were collected with an inoculation loop in cooled sterile sodium chloride, vortexed, and washed twice by centrifugation for 5 min at 6.000 g. Last, the bacteria were suspended in sterile water and their cell concentrations were determined using a Neubauer hemocytometer.

Prior to the application of bacteria and fungi, the mosquito larvae were exposed to an antibiotic cocktail (amikacin (OJSC “Sintez,” RF) at 10 mg/L and penicillin (PanReac, Applichem) 10 mg/L) for 24 h. Then, the water containing the antibiotics was exchanged with sterile tap water. The eradication efficacy was controlled by plating larval homogenates on Nutrient agar as described in the section called “CFU Counts and Identification of Cultivable Bacteria.” Suspensions of conidia and bacterial cells were added separately or in combination to containers containing the mosquito larvae. The final concentrations were 5 × 108 bacterial cells and 1 × 106 conidia per milliliter of water. The control was treated with the equivalent amount of sterile water. Thus, the experiment with each bacteria included four treatments: control, bacteria, fungus, and fungus + bacteria. The mortality data were collected daily for 6 days. At least 30 insects (1 replicate included 10 larvae) from each of the treatments were used for the assays.

Statistical Analysis

The differences in the survival of the mosquito larvae were analyzed by the log-rank test followed by a Holm-Sidak adjustment. The synergistic and antagonistic effects between the fungus and insecticide as well as between the fungus and bacteria were determined by comparing the observed and expected mortality using the χ2 criterion, as described by Robertson and Preisler [35]. A comparison of portions of larvae in which hyphal bodies were detected and not detected was performed using Fisher’s exact test. Data on the bacterial OTU abundance, total 16S rRNA, CFU count, and antagonistic activity of the bacteria in vitro were checked for normal distribution using a Shapiro-Wilk W test. The MiSeq data were analyzed by the two methods: (i) comparisons of relative abundances and (ii) comparisons of actual read counts per taxon after rarefying. The effects were considered as significant (P < 0.05) if they were registered in the both cases only. The data for predominant taxa had normal distribution and were analyzed by the two-way ANOVA followed by Tukey’s post hoc test. The data for subdominant taxa had mainly abnormal distribution and were analyzed using a nonparametric analog of the two-way ANOVA—Scheirer-Ray-Hare test [36], followed by Dunn’s post hoc test. In the results, the levels of significance are presented for the relative abundances comparisons. Data on total 16S rRNA and CFU count were also analyzed by the Scheirer-Ray-Hare test. Differences in the antagonistic activity of the bacteria towards M. robertsii in vitro were determined by the one-way ANOVA followed by Tukey’s test. The software PAST 3 [37], SigmaStat 3.1 (Systat Software Inc., USA), STATISTICA 8 (StatSoft Inc., USA), and AtteStat v.12.5 [38] were used for the analyses.

Results

Mortality and Colonization Assay

The mortality of the untreated larvae was 3.3% on the 6th day posttreatment (Fig. 1a). Fungal infection led 50.8% mortality of mosquito larvae, and treatment with avermectins led to 46.7% mortality by the 6th day posttreatment. The mosquito mortality increased significantly after the combined treatment (85% at the 6th day posttreatment), and a synergistic effect was registered from the 3rd to the 6th days (χ2 > 6.5, df = 1, P < 0.001). The log-rank test also showed significant differences between the combined treatment and treatments with avermectins or fungus alone (χ2 > 9.9, df = 1, P < 0.001). The median-lethal survival time (LT50) decreased 1.5-fold (from 6 to 4 ± 0.2 days) after the combined treatment, compared with the single treatments. Thus, the effects in mosquito mortality were consistent with those in our previous work [30].

Fig. 1
figure 1

Mortality dynamics of Aedes aegypti larvae and a colonization assay. a—Dynamic of Aedes aegypti larval mortality after separate and/or combined treatments with the fungus Metarhizium robertsii (1 × 106 conidia/mL) and avermectins (6 μg/L). Different letters indicate significant differences between treatments (log-rank test, χ2 > 9.9, df = 1, P < 0.001). The asterisks indicate a synergistic effect on the larval mortality between the fungus and avermectins (χ2 > 6.5, df = 1, P < 0.01). b—Proportion of freshly dead larvae in which hyphal bodies were detected (HB-positive) and not detected (HB-negative) after treatment with the fungus alone (f) and in combination with avermectins (f + av). The asterisk (*) indicates a significant difference between treatments (P = 0.014, Fisher’s exact two-sided test). c—Electron microscopy of the gut lumen showing the conidia and germ tubes (GT). d, e—Electron microscopy of a hemocoel showing the presence of hyphal bodies. Scale bar, 5 μm

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Fungal germ tubes and hyphal bodies were detected in both the gut lumen and the hemocoel (Figs. 1c–e). The number of hyphal body–positive larvae was significantly higher after the combined treatment compared with the treatment with fungus alone by the 3rd and 4th days posttreatment (Fisher’s exact two-sided test, df = 1, P = 0.014, Fig. 1b). At the 5th–6th days posttreatment, this trend was also observed, but the differences between treatments were insignificant (P = 0.23). No hyphal bodies were detected in the fungus-free treatments.

Changes in the Bacterial Communities After Fungal and Avermectin Treatments

The classification based on 16S rRNA sequencing revealed 215 operational taxonomic units (OTUs) in mosquito larvae that were grouped into 73 genera, 48 families, and 11 classes (Appendix A). Three classes were the most abundant, namely Flavobacteria (phylum Bacteroidetes), Actinobacteria (phylum Actinobacteria), and Gammaproteobacteria (phylum Proteobacteria). The most abundant genus (51.6%) was Chryseobacterium (Flavobacteriaceae), which was represented by five OTUs. In addition, two other genera, Microbacterium (Microbacteriaceae) as represented by only one OTU (abundance 13.9%) and Aeromonas (four OTUs, abundance 13.4%), were identified among the predominant ones.

The number of OTUs decreased significantly under the influence of fungal infection (two-way ANOVA, effect of fungus: F1.12 = 7.0, P = 0.02, Table 1), and by contrast, the influence of avermectins led to an increase in the number of OTUs (F1.12 = 28.8, P = 0.0002, Table 1). Under fungal infection, we observed a trend towards an increase in the Shannon index (F1.12 = 2.9, P = 0.11), but treatment with avermectins led to a decrease in the index (F1.12 = 6.4, P = 0.03). Fungal infection decreased the Chao1 index (F1.12 = 5.5, P = 0.04), but treatments with avermectins led to an increase in this index (F1.12 = 13.0, P = 0.004). No significant interactions were observed between the two factors on the diversity indexes.

Table 1 Diversity characteristics of bacterial communities in Aedes aegypti larvae at 48 h posttreatment with avermectins, Metarhizium robertsii, and their combination
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Treatments with M. robertsii and avermectins led to significant shifts in the structure of the mosquito microbiota (Fig. 2). Regarding the predominant groups, fungal infection led to a decrease in the relative abundance of the most abundant group (Flavobacteria, Chryseobacterium), while toxicosis caused by avermectins led to an increase in the abundance of this group of bacteria (effect of the fungus: F1.12 = 7.8, P = 0.015; effect of the avermectins: F1.12 = 46.5, P < 0.0001, Fig. 2a, b); however, the factor interaction between the fungal and avermectin treatments was not significant (F1.12 = 3.4, P = 0.09). After the fungal treatment, we observed a sharp increase in the abundance of Gammaproteobacteria, which was represented primarily by Aeromonas (Tukey’s HSD, P < 0.0005 compared with the other treatments), but we did not observe this elevation after the combined treatment with fungus and avermectins (factor interaction F1.12 = 88.4, P < 0.0001), i.e., avermectins limited the Aeromonas increase caused by fungal infection. Importantly, the avermectin treatment led to a significant 3.3–3.6-fold decrease in the relative abundance of Actinobacteria, which were primarily represented by Microbacterium (F1.12 = 12.4, P = 0.004).

Fig. 2
figure 2

Changes in the bacterial communities of Aedes aegypti larvae whole-body homogenates at 48 h posttreatment with Metarhizium robertsii conidia, avermectins, and their combination. a—Relative abundance of the bacterial classes. b—Relative abundance of the genera. Different letters indicate significant differences between treatments for specific groups of bacteria, as calculated for 4 biological replicates (Tukey’s post hoc test, P < 0.05). c—Principal component analysis for the OTU level

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Regarding the less abundant groups, the fungal treatment led to a significant decrease in the relative abundance of Alphaproteobacteria and increased Sphingobacteria (F1.12 > 4.9, P < 0.05, Fig. 2a) as well as the elevation of certain Gammaproteobacteria such as Acinetobacter and unc. Enterobacteriaceae (H1.15 > 11.3, P < 0.001, Appendix B, Fig. S2). Under the influence of avermectins, a decrease in the abundance of Alphaproteobacteria followed by an increase in the abundance of Betaproteobacteria was observed (F1.12 > 10.5, P < 0.007, Fig. 2a). In particular, a decrease in the proportion of subdominant Roseomonas and unc. Rhizobiales (Alphaproteobacteria) was accompanied by a significant increase in the abundance of a number of low-abundance bacteria, namely Vogesella, Massilia, unc. Comamonadaceae, unc. Burkholderiales, and Pseudoduganella (Betaproteobacteria) (H1.15 > 4.4, P < 0.035, Appendix B, Fig. S2). In addition, avermectin treatment led to a significant increase in the proportion of Pseudomonas (Gammaproteobacteria) as well as Brevundimonas and Asticcacaulis (Alphaproteobacteria) (H1.15 > 3.8, P < 0.05, Appendix B, Fig. S2).

A principal component analysis (PCA) showed a clear distance between the bacterial communities of the control group, the group treated with the fungus, and the groups treated with avermectins (Fig. 2c). Larval bacterial communities treated with avermectins and the combination (avermectins + fungus) were significantly overlapped, which confirms the higher similarity of the bacterial communities between these two groups. The first component explained 73% of the variation, and OTU-1 (Chryseobacterium) made the largest contribution. The second component explained 22% of the variation, with the largest contributions from OTU-2 (Microbacterium) and OTU-6 (Aeromonas).

Total Bacterial Load and Identification of Cultivable Bacteria

The total bacterial load in mosquito larvae from different treatments was analyzed by measuring the bacterial 16S rRNA (qPCR) and counting the bacterial CFUs on different media. Both analyses revealed a significant increase in the bacterial load under toxicosis caused by avermectins (Fig. 3). Specifically, the total bacterial 16S rRNA increased significantly under the influence of avermectins and was insignificant under the influence of the fungus (H1.27 = 5.7, P = 0.01 and H1.27 = 1.8, P = 0.18, respectively). The plating of larvae homogenates on nonselective blood agar also showed a significant increase in the CFU count under avermectin treatment (H1.19 = 8.7, P = 0.003) and insignificant elevation under fungal infection (H1.19 = 0.3, P = 0.59). No significant factor interactions between the fungus and avermectins on the bacterial load was revealed. Similar effects were obtained for the CFU counts on Endo agar, Flavobacteria media, and Aeromonas media (Appendix B, Fig. S3).

Fig. 3
figure 3

Total bacterial load for whole-body homogenates of Aedes aegypti larvae at 48 h posttreatment with Metarhizium robertsii conidia, avermectins, and their combination. a—16S rRNA normalized expression of two mosquito reference genes, Rsp17 and Rp49. b—CFU count on blood agar. Different letters above each column indicate significant differences between treatments (Dunn’s test, P < 0.05)

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To establish the effects of the bacteria on the development of mycosis, we isolated and identified the bacteria from the predominant groups present in the microbiome, primarily Chryseobacterium, Microbacterium, Aeromonas, and Delftia. From the Chryseobacterium genus, we identified four isolates of C. cucumeris (Appendix B, Table S2) that were obtained from blood agar and Flavobacteria media. Among the Microbacterium, two isolates of M. paraoxydans were obtained from blood agar. From the Delftia genus, we isolated six cultures from Endo agar and Aeromonas media. These cultures demonstrate 100% shared identity for the 16S rRNA sequences between two species, Delftia tsuruhatensis and D. lacustris. In addition, Pseudomonas alcaligenes, P. putida, P. protegens, P. aeruginosa, P. mosselii, Stenotrophomonas maltophilia, and Acinetobacter sp. were isolated from different media (Appendix B, Table S2). We could not isolate any Aeromonas cultures using the media mentioned above. Primarily, Pseudomonas colonies were obtained from the Aeromonas media. Therefore, we used a museum strain of Aeromonas hydrophila (see section called “Antagonistic Effects of the Cultivable Bacteria Towards Fungus In Vitro”) in the subsequent experiments.

Antagonistic Effect of Cultivable Bacteria Towards Metarhizium robertsii In Vitro

An analysis of interactions between the cultivable bacteria and M. robertsii using an agar plug assay showed that all of the bacteria exhibit antagonistic effects of varying strength (Fig. 4, see also Appendix B, Fig. S4). The weakest antagonism was registered for C. cucumeris, which only inhibited fungal growth to 0.4 ± 0.07 mm. The strongest antagonism was exhibited by M. paraoxydans (6.9 ± 0.4 mm), and it was significantly different from that of the other bacteria (Tukey’s test, P < 0.001). The bacterium A. hydrophila also showed a relatively strong antagonistic effect towards M. robertsii (3.4 ± 0.07 mm). Cultures of Delftia sp. and P. putida inhibited fungal growth to 2.3 ± 0.18 mm and 1.4 ± 0.12 mm, respectively.

Fig. 4
figure 4

Antagonistic effect of predominant bacteria from Aedes aegypti larvae towards Metarhizium robertsii as estimated by agar plug method. Cc, Chryseobacterium cucumeris; Ah, Aeromonas hydrophila; Mp, Microbacterium paraoxydans; D, Delftia sp.; and Pp, Pseudomonas putida. Different letters indicate significant differences (Tukey’s test, P < 0.05)

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Combinative Effects of Bacteria and M. robertsii on the Mortality of Mosquito Larvae

Treating with the antibiotic cocktail significantly inhibited the bacterial associates of the Ae. aegypti larvae. No bacterial colonies were registered after plating the larvae treated with the antibiotics on LB media. Treatment with antibiotic cocktail had no effect on the larval survival throughout the experiment (Fig. 5S). Larvae treated with antibiotics were more susceptible to M. robertsii compared with native larvae. A significant synergistic effect between the antibiotics and fungus was observed from the 5th to 7th days posttreatment (χ2 > 33.6, df = 1, P < 0.05; Fig. S5).

Fig. 5
figure 5

Mortality dynamics of germ-free Aedes aegypti larvae treated with conidia from Metarhizium robertsii (1 × 106 conidia/mL), cultivable bacteria (5 × 108 cells/mL), and their combination. The control treatment included mosquito larvae pre-treated with antibiotic cocktail (amikacin + penicilin) for 24 h. a—Chryseobacterium cucumeris; b—Aeromonas hydrophila; c—Microbacterium paraoxydans; d—Delftia sp.; and e—Pseudomonas putida. Asterisks indicate significant antagonistic or synergistic effects between the bacteria and fungus on the mortality of the mosquito larvae (χ2 > 3.85, df = 1, P < 0.05). Different letters next to each line indicate significant differences between treatments as estimated by log-rank test (P < 0.05)

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In the following experiments, we studied the combined effects between cultivable bacteria and M. robertsii on larvae that were pretreated with antibiotics. None of the tested bacteria caused larval mortality compared with the antibiotic-treated control (Fig. 5). However, treatments with different bacteria along with the M. robertsii conidia led to synergistic, antagonistic, or neutral effects on the mortality of Ae. aegypti larvae. Specifically, treating the larvae with C. cucumeris did not have any effect on the larval mortality compared with the fungal treatment alone (log-rank test, χ2 < 0.9, df = 1, P > 0.34) (Fig. 5a). Treating with A. hydrophila led to a slight decrease in susceptibility to fungal infection. A weak but significant antagonistic effect from the 3rd to 5th days posttreatment was registered (χ2 > 6.8, P < 0.01) (Fig. 5b). Importantly, the mortality of fungus-treated larvae was significantly reduced after treating with M. paraoxydans (Fig. 5c). A significant antagonistic effect was recorded from the 4th to 6th days posttreatment (χ2 > 6.5, P < 0.01). The reintroduction of Delftia sp. also led to reduced mortality due to the fungus (Fig. 5d). A significant antagonistic effect was registered from the 5th to 6th days posttreatment (χ2 > 6.9, P < 0.01). The mortality rate of the conidia-treated larvae was significantly higher after the reintroduction of P. putida (Fig. 5e). A significant synergistic effect was observed from the 2nd to 6th days posttreatment (χ2 > 4.5, P < 0.04).

Discussion

This study shows significant changes in the structure of the bacterial community of Ae. aegypti larvae under the influence of avermectins and M. robertsii infection. We suggest that the synergy between these agents is linked to the shifts in the bacterial composition. In particular, avermectins decreased the relative abundance of strong fungal antagonists (Actinobacteria, Microbacterium) and increased the abundance of bacteria with neutral effects on the fungus (Flavobacteria, Chryseobacterium), which may create favorable conditions for the differentiation of the fungal infection structures and promote a more active penetration of the fungus through the gut wall into the hemocoel. It should be noted that there are contrasting data on the germination of fungal conidia in the gut of Ae. aegypti larvae and the colonization of the hemocoel by hyphal bodies in experiments by various researchers. In particular, Butt and coauthors [26] observed conidia accumulation in the larval gut without the differentiation of fungal structures, while Riba and coworkers [29] registered typical mycosis with hyphal growth. In our previous study [30] on the same laboratory line of Ae. aegypti (as in the present study), we observed a colonization of the hemocoel by hyphal bodies of M. robertsii after treating with the fungal conidia. The hyphal bodies were recorded for both living and recently dead larvae [30]. The proportion of hyphal body–positive larvae in the late stages of pathogenesis was high (more than 83%), which indicates the stability of fungal colonization for this line of mosquitoes. It is possible that contrasting data on the colonization of mosquito larvae may be associated with significant differences in the microbiome structures of different mosquito lines.

Significant variation in the composition of bacterial communities in natural and laboratory populations of Ae. aegypti larvae has been shown [40, 41]. The bacterial communities of Ae. aegypti larvae are mostly represented by three primary phyla: Bacteroidetes, Actinobacteria, and Proteobacteria. However, the composition and abundance of different classes, families, and genera varied significantly [40, 42]. The high abundance of Chryseobacterium and Microbacterium was shown for some laboratory lines of Ae. aegypti [42], which is consistent with our research. In the present study, we registered the OTUs of some groups, such as Burkholderiales, Comamonas, and Rhizobium, that may be in a mutualistic relationship with insects and may constitute a significant part in the reproductive organs, salivary glands, or guts [43,44,45]. However, there is no evidence that different mosquito populations have a particular set of bacteria that is typical for all individuals, regardless of the habitat [46].

It has been previously shown that biological (Bacillus thuringiensis) and chemical (methoprene) insecticides led to specific shifts in the bacterial communities of mosquito larvae [10]. Аvermectins affect glutamate and other ligand-gated and voltage-dependent chloride channels in invertebrates [47], and they also cause the inhibition of cellular immunity [48] and the destruction of intestinal epithelial cells [49]. In addition, this insecticide leads to a decrease in food consumption and thereby causes starvation, which was shown in studies on terrestrial insects [50]. Slowing the passage of food through the gut leads to the creation of more isolated and less aerated conditions for the development of bacteria as well as to changes in the pH and other physicochemical parameters of the microenvironment. Moreover, avermectins cause dysregulation in the humoral immunity and detoxification systems [30, 48, 51], which may also lead to a change in the total bacterial load and the microbiome structure in the gut and other organs.

After the avermectin treatment, we observed an increase in the total bacterial load of the larvae, which was accompanied by an increase in the number of OTUs, the Chao index, and a decrease in the Shannon index. We observed shifts in the community structure towards an increase in the abundance of Flavobacteria and Betaproteobacteria. An increase in the total bacterial load may correlate with a decrease in the Shannon index, since the proliferation of certain groups of bacteria leads to the crowding out of less abundant groups. This trend was shown, for example, in the wax moth Galleria mellonella under the influence of another neurotoxin (Habrobracon hebetor venom) [17]. Importantly, Aedes larvae are able to digest bacteria, in particular Flavobacteria [52]. Therefore, an increase in the total bacterial load and especially Chryseobacterium is probably associated with a decrease in digestive activity caused by the destruction of the gut epithelium and the disturbance in the enzymatic system under the influence of avermectins. The elevation of the Betaproteobacteria abundance was due to subdominant bacteria that primarily belonged to Burkholderiales (Massilia, Comamonadaceae, unc. Burkholderiales). This effect remains unclear. It was shown by Kikuchi and coworkers [53], and Muturi and coworkers [54], that Burkholderiales abundance and diversity might increase in different environments (water, soil) after an insecticide treatment. These authors suggest that Burkholderiales can use insecticides as a carbon source. However, the ability of these bacteria to utilize avermectins has not been studied.

Fungal infection led to a significant decrease in the diversity indexes of the bacterial communities and a trend towards the elevation of total bacterial 16S rRNA was registered. Previously, an enhancement in the bacterial load and slight decrease of the diversity indexes were observed during the topical infection of mosquito adults with Beauveria and Isaria fungi, which was associated with the modulation of immune responses [6, 25]. Interestingly, the proportion of Aeromonas was strongly increased by fungal infection. We believe that Aeromonas develops in water or in the gut lumen due to the excess of organics, associated with the introduction of fungal conidia. It is well known that Aeromonas is more abundant in eutrophic water bodies [55,56,57,58]. In addition, Aeromonas exhibits high chitinolytic activity and is able to use chitin as a carbon source [59]. Brzezinska and Donderski [57] showed that Aeromonas was predominant among other chitinolytic bacteria in freshwater bodies and especially in eutrophic lakes. Therefore, the elevation of Aeromonas may be caused by an increase in the fungal chitin content after M. robertsii treatment. It is noteworthy that the larvae treated with the combination of the fungus and avermectins did not show a high abundance of Aeromonas. This result correlates with the fact that under the influence of avermectins, Ae. aegypti larvae accumulate fewer fungal conidia compared with larvae treated with fungus alone [30]. Interestingly, mycosis development was often accompanied by an increase in the abundance of chitinolytic bacteria in insects, such as Serratia marcescens [6], Erwinia [16], and Aeromonas (present study).

The changes in the bacterial community of Ae. aegypti larvae under the influence of M. robertsii may also be associated with the microbiome of the fungus. Bacterial communities of entomopathogenic fungi are poorly studied. However, Chen et al. [60] showed that the bacteriomes of the entomophthoralean fungus Pandora are represented primarily by Enterobacteriaceae and Acinetobacter. According to our preliminary data, the conidia of Metarhizium are characterized by a relatively rich bacteriome (> 70 OTUs) and by a high abundance of Enterobacteriaceae and Acinetobacter (Appendix B, Fig. S6). This result correlates with the fact that fungal treatment increased the abundance of unc. Enterobacteriaceae and Acinetobacter in Ae. aegypti larvae (Appendix B, Fig. S1).

Bioassays on the predominant bacteria showed different strengths of antagonism to M. robertsii in in vitro tests and different effects (from antagonism to synergism) under the combined larval treatment when using the bacteria and M. robertsii. Germ-free larvae were more susceptible to fungus than native larvae (Appendix B, Fig. S5). This finding is highly consistent with other studies [19], which show the contribution of Blattella germanica gut bacteria to fungal resistance after the oral administration of Metarhizium anisopliae. Most importantly, following avermectin treatment, the abundantly proliferating Chryseobacterium was relatively inert to the fungus, i.e., it did not have an antagonistic effect on larval mortality and showed the weakest antagonism in vitro (Fig. 4, Fig. S4). However, Microbacterium (Actinobacteria), which decreased under avermectin toxicosis, was the strongest antagonist of the fungus in both in vitro and in vivo assays. We suggest that the decrease in Actinobacteria abundance after avermectin treatment could have caused a decrease in fungistatic activity in mosquito larvae and contributed to a more active differentiation of the infectious fungal structures. Actinobacteria are known to secrete broad-spectrum metabolites that exhibit antifungal activity [61, 62]. In particular, Microbacterium produces isoflavones (Genestin and Daidzin) with activity against the phytopathogenic ascomycete Phyllosticta citricarpa [63]. The ability of Microbacterium to reduce the growth of Aspergillus [64, 65], Penicillium [66], and Candida albicans [67] was shown, and here we demonstrate antagonistic activity against Metarhizium for the first time. Regarding other bacteria, Aeromonas showed antagonism towards Metarhizium in an in vitro test and weak antagonism in a bioassay on Ae. aegypti larvae. The increase in Aeromonas abundance was impeded by avermectins after the combined treatment, which may also have had an impact on the promotion of fungal infection. The bacterium Delftia exhibited antagonism during the coinfection assay; however, the abundance of these bacteria in the microbiome structure did not change significantly under the influence of the fungus and avermectins. Therefore, the contribution of Delftia to the synergism between these agents is not obvious. Among the subdominant bacteria, we observed an increase in the abundance of Pseudomonas after avermectin treatment. These bacteria showed strong synergism with the fungus on mosquito mortality, despite their antagonistic interactions in vitro. Previously, a synergistic effect between Beauveria bassiana and Pseudomonas sp. was shown on locusts despite their antagonistic effect in vitro [68]. This finding confirms the more complicated relationships between fungi and bacteria in insects compared with direct interactions under cocultivation on artificial media.

In conclusion, this is the first study to show changes in the bacterial communities of mosquitoes in response to the combined action of insecticides and entomopathogenic fungi. The obtained results indicate the significant effects of both Metarhizium and avermectins on the microbiota in Ae. aegypti larvae, and these changes are expressed both as changes in the total bacterial load and in the diversity and structure of the bacterial community. The influence of avermectins led to a shift in the bacterial community that was more favorable for the development of fungal infection. In particular, it reduces the abundance of fungal antagonists (Actinobacteria) and increases the abundance of bacteria with a neutral effect on Metarhizium (Flavobacteria). The latter was correlated with more active differentiation of fungal infection structures, and, accordingly, the faster death of the larvae after combined treatment with insecticide and the fungus. Future studies may focus on functional changes in the microbial community under the influence of insecticides and entomopathogenic fungi. It should be noted that some bacteria (Aeromonas) are potential pathogens of vertebrates, and they demonstrated a sharp increase after M. robertsii treatment. Therefore, subsequent studies may also focus on changes in the abundance of these bacteria in water bodies after fungal treatments against mosquito larvae.