Skip to main content
Download PDF

Interspecies microbiome transplantation recapitulates microbial acquisition in mosquitoes

Microbiome volume 10, Article number: 58 (2022) Cite this article

Abstract

Background

Mosquitoes harbor microbial communities that play important roles in their growth, survival, reproduction, and ability to transmit human pathogens. Microbiome transplantation approaches are often used to study host-microbe interactions and identify microbial taxa and assemblages associated with health or disease. However, no such approaches have been developed to manipulate the microbiota of mosquitoes.

Results

Here, we developed an approach to transfer entire microbial communities between mosquito cohorts. We undertook transfers between (Culex quinquefasciatus to Aedes aegypti) and within (Ae. aegypti to Ae. aegypti) species to validate the approach and determine the number of mosquitoes required to prepare donor microbiota. After the transfer, we monitored mosquito development and microbiota dynamics throughout the life cycle. Typical holometabolous lifestyle-related microbiota structures were observed, with higher dynamics of microbial structures in larval stages, including the larval water, and less diversity in adults. Microbiota diversity in recipient adults was also more similar to the microbiota diversity in donor adults.

Conclusions

This study provides the first evidence for successful microbiome transplantation in mosquitoes. Our results highlight the value of such methods for studying mosquito-microbe interactions and lay the foundation for future studies to elucidate the factors underlying microbiota acquisition, assembly, and function in mosquitoes under controlled conditions.

Video Abstract

Background

A substantial body of evidence has emerged revealing the importance of microbiota to the biology of the animal hosts they associate with, which has stimulated broad interest in understanding the assembly of these communities. However, the daunting complexity of the microbiota present in many higher eukaryotes and the lack of conventional microbiology techniques to culture these microbes have limited our ability to address important questions in the field. As such, the mechanisms facilitating host-microbe interactions and the functional role of the microbiome as a holistic unit are poorly elucidated. Microbiota transplantation approaches are one promising technique for basic research and therapeutics, but studies employing these techniques have mainly been undertaken in mammalian systems [1,2,3,4,5,6], and there has been little attempt to transfer these approaches to medically or agriculturally important insects.

Microbiome research has expanded in mosquitoes given their medical relevance and interesting biology. As holometabolous insects, mosquitoes have distinct aquatic and terrestrial life stages, including larvae that molt through four aquatic instars before pupating on the water’s surface and emerging as terrestrial adults [7, 8]. All of these stages harbor gut microbial communities dominated by bacteria that can vary tremendously in diversity and abundance over time and space [9]. Larvae acquire their gut microbiota from their aquatic environment during feeding [10,11,12,13,14], after which bacteria experience periods of extreme turnover as parts of the larval gut are continuously shed and replaced during feeding, molting, and metamorphosis to the adult stage [15, 16]. The adult gut, in contrast, is initially seeded by bacteria from larvae and/or the larval environment but thereafter may be modulated by adult sugar and blood feeding activities [9], the latter of which underlies the ability of adult female mosquitoes to acquire and transmit disease-causing pathogens to humans [17]. While most of the larval and adult mosquito microbiota is thought to be restricted to the midgut [18,19,20,21], bacteria and other microbes are also known to colonize other mosquito tissues [22,23,24,25]. These include the common bacterial endosymbiont Wolbachia, which infects the germline of Culex quinquefasciatus and two Anopheles species, but not Aedes aegypti, and is transovarially transmitted to offspring each generation [26,27,28,29,30,31,32].

Altogether, the microbiota associated with the mosquito gut and other tissues can have profound impacts on mosquito biology by modulating larval growth and development [10, 12, 33,34,35] as well as adult survival [36,37,38], reproduction [33, 39], and the competency of adult female mosquitoes to transmit human pathogens [40]. As such, there is a growing interest in exploiting microbes for vector control [41,42,43]. However, available tools to manipulate the microbiota in mosquitoes are limited, lagging behind research in other systems [44,45,46,47]. Antibiotic treatment has been commonly used to perturb microbiota for experiments investigating tripartite interactions between mosquitoes, their microbiota, and human pathogens. While these experiments have provided insights into the role of bacteria in mosquito vector competence [40, 48,49,50], the use of antibiotics has its limitations. For example, some bacteria may not be susceptible to the antibiotics, meaning these approaches alter the microbiota rather than eliminate all microbiota [12, 51]. Furthermore, antibiotics can have off-target effects on host physiology and can affect mitochondria [52,53,54,55]. Alternatively, introduction of specific bacterial taxa into mosquito larvae or adults can be achieved by spiking the larval water or sugar solution, respectively [56,57,58]. However, while these approaches are effective at transferring specific bacterial taxa to mosquitoes, they likely do not reflect acquisition processes that occur in the field and can only be undertaken with culturable microbes.

We previously developed an approach to generate and maintain gnotobiotic mosquitoes colonized by individual bacterial taxa by sterilizing the surface of mosquito eggs and inoculating water containing bacteria-free (axenic) larvae hatched from surface-sterilized eggs under sterile conditions [10]. Similarly, the generation of axenic adult mosquitoes that can thereafter be inoculated with individual bacterial taxa via a sugar meal has been undertaken using heat-killed bacteria, supplementation of axenic larval cultures with eukaryotes, or reversible colonization [34, 59,60,61]. While these approaches have been used to broadly examine the biology of mosquito-microbe interactions and decipher the role of bacterial microbiota on host biology [10, 12, 21, 33, 34, 62,63,64], expanding these techniques to transfer complete or tailored microbial communities would be highly desirable.

Here, we developed an approach to transfer entire microbial communities between mosquito cohorts. We undertook transfers between (Cx. quinquefasciatus to Ae. aegypti) and within (Ae. aegypti to Ae. aegypti) species to validate the approach and determine the number of mosquitoes required to prepare donor microbiota. We chose to utilize these species in our experiments for two reasons. First, both Ae. aegypti and Cx. quinquefasciatus are biomedically relevant vector species that are commonly studied in the laboratory [7]. Previous studies have also carefully characterized microbiota acquisition and assembly across Ae. aegypti life history [10]. Second, while Cx. quinquefasciatus mosquitoes are readily infected by Wolbachia in the laboratory and commonly exhibit natural infections in the field [27, 29], Ae. aegypti mosquitoes are generally recalcitrant to infection and are not known to harbor natural infections [28, 30]. By introducing microbiota derived from both Ae. aegypti and Cx. quinquefasciatus donors into Ae. aegypti recipients, we could therefore also establish whether our transplantation approach (i) recapitulated patterns of microbiota assembly and persistence previously observed in Ae. aegypti (positive control) and (ii) supported the expectation that we would not be able to successfully transfer Wolbachia from Cx. quinquefasciatus donors to Ae. aegypti recipients (negative control). Altogether, our results demonstrate the transfer of a complete microbiota from one mosquito cohort to another and lay the foundation for future studies to examine microbiota assembly and function in mosquitoes colonized by defined microbiomes with potential for exploitation for mosquito and disease control.

Methods

Donor sample collection and preparation of donor pools for microbiota transplantation

Laboratory-colonized Ae. aegypti (Galveston) and Cx. quinquefasciatus (Houston) mosquitoes used as donors in this study were maintained in the same insectary and reared under the same conditions as described previously [63]. The Ae. aegypti colony, collected in Galveston, Texas, had been reared in the insectary for over 10 years, while the Cx. quinquefasciatus colony, collected in Houston, Texas, had been reared for 17 generations. In order to characterize microbiota diversity in both donor species, 150 individual 3- to 4-day-old sugar-fed adult females of each species were collected, surface sterilized by immersing in 70% ethanol for 5 min followed by 3- to 5-min washes in sterile 1X PBS, and stored at −20 °C for downstream sequencing. Adult mosquitoes from both species were also used to generate donor pools for microbiota transplantation. In brief, cohorts of 10, 20, 40, or 80 3- to 4-day-old adult female mosquitoes were collected, surface-sterilized in 70% ethanol for 5 min, rinsed three times in sterile 1X PBS for 5 min, and transferred individually to sterile 2-ml safe lock tubes (Eppendorf, Hamburg, Germany) containing 5 mm steel beads and 500 μl of sterile 1X PBS (Fig. 1). Tubes were then homogenized at a frequency of 26 Hz/s for 1 min, briefly centrifuged to collect debris, and 50 μl of the homogenate from each tube was pooled (Fig. 1). Pooled homogenates were subsequently centrifuged at 5000 × g for 5 min to pellet any remaining debris, and the resulting supernatant was passed through a 5 μm filter to produce a final filtrate for transplantation. Filtrates, which ranged in volume from 500 μl (pool of 10) to 4 ml (pool of 80), were finally adjusted to a total volume of 50 ml using sterile water, and we repeated the entire process a total of three times to produce a total of 150 ml of each donor pool prior to use in downstream experiments (Fig. 1). A 200 μl aliquot of each pool was also retained and immediately subjected to genomic DNA isolation using a NucleoSpin Tissue Kit (Machery-Nagel, Düren, Germany). The resulting DNA was then stored at −20 °C for downstream sequencing.

Fig. 1
figure 1

Overview of methodology used to perform inter- and intra-species microbiota transplantations in mosquitoes. (Left) Preparation of Ae. aegypti and Cx. quinquefasciatus donor pools. Individual 3–4-day-old sugar-fed adult females from our standard laboratory colonies were collected, surface-sterilized, and homogenized (1). Individual homogenates were then pooled and centrifuged to collect debris prior to filtering of the resulting supernatant to produce a final filtrate (2). Filtrates, which ranged in volume from 500 μl (pool 10) to 4 ml (pool 80), were then adjusted to a total volume of 50 ml using sterile water prior to transplantation (2). (Right) Transplantation of donor pools into a focal host species (Ae. aegypti). Eggs laid by blood-fed adult females from the standard laboratory colony were surface-sterilized and hatched in sterile water to produce axenic larvae (3). Larvae were then transferred to replicate flasks (n = 5) containing a 50 ml suspension of a given donor pool and provided sterilized diet every other day until pupation (4). Pupae produced from replicate flasks containing the same donor pool were finally pooled in water from the larval rearing flasks and transferred to a sterile plastic chamber for adult emergence (5). Donor and recipient samples collected for sequencing are indicated in bold. See “Methods” for more information. Created with BioRender.com

Full size image

Microbiota transplantation and recipient sample collection

Axenic (microbe-free) Ae. aegypti (Galveston) L1 larvae served as the recipient host for all transplantations. In brief, axenic larvae were prepared by submerging eggs in 70% ethanol for 5 min, then transferred to a solution of 3% bleach and 0.01% Decon-Quat 200V (Ab Scientific Ltd) for 3 min, followed by a wash in 70% ethanol for 5 min, and finally rinsing three times in sterile water (Fig. 1). Eggs were then transferred to sterile water and vacuum hatched in sterile containers. Twenty axenic first instar larvae were then transferred to each of five T75 vented tissue culture flasks (Thermo Fisher Scientific, Waltham, MA, USA) containing 50-ml suspension of a given donor pool (described above) and 60 μl of autoclaved powdered TetraMin pellets (Tetra, Melle, Germany) reconstituted with sterile water to a final concentration of 1 mg/ml (Fig. 1). In addition to the donor treatments, a negative control was done, whereby larvae were transferred to flasks containing sterile water and diet only (i.e., no microbes) and maintained alongside experimental flasks. All larvae (control and experimental) were provided sterilized diet every 2 days until the treatment groups pupated (the control group did not pupate and died at L2 or L3), while water from control flasks was used to screen for contamination throughout the experiment as described previously [10]. Flasks were maintained at 70% humidity and 27 °C.

In order to assess successful microbiome transplantation, four sets of recipient samples were collected for sequencing: (i) 200 μl of larval water from each replicate flask, collected when larvae had molted to the third instar, (ii) third instar larvae (pools of 5) collected from the same flasks, and at least three individual sugar-fed adult females that had emerged from pupae either (iii) 3 or (iv) 6 days prior to collection. Pupae produced from replicate flasks containing the same donor pool were pooled and transferred to sterile water in a sterile plastic chamber for adult emergence. Newly emerged adults were provided 10% sucrose in sterile water ad libitum until collection as described above. Total genomic DNA was extracted from all recipient samples using a NucleoSpin Tissue Kit (Machery-Nagel, Düren, Germany). Larvae and adults were surface sterilized as described above before DNA isolation.

Amplicon library construction, sequencing, and data analysis

Subsamples from the DNA extracts were used for amplifying the V3-V4 region of the bacterial 16S rRNA gene using primers 341F (CCTACGGGNGGCWGCAG) and 805R (GACTACHVGGGTATCTAATCC) [65], followed by PCR amplification for Illumina sequencing. Samples were paired-end sequenced (2 × 250 bp) on an Illumina MiSeq. Sequence reads were processed using the DADA2 pipeline in QIIME 2-2019.4 [66, 67]. In brief, sequence reads were first filtered using DADA2’s recommended parameters and an expected error threshold of 0.5. Filtered reads were then de-replicated and denoised using default parameters. After building the ASV table and removing chimeras and low-abundance (< 0.005%) ASVs, taxonomy was assigned using a Naive Bayes classifier natively implemented in QIIME 2-2019.4 and pre-trained against the Greengenes reference database (13.8) [68, 69]. A phylogenetic tree was built using FastTree (v2.1.3) [70] from a multiple sequence alignment made with the MAFFT alignment tool [71] against the Greengenes core reference alignment [72]. Patterns of alpha diversity (as measured by Shannon’s H index and ASV richness) and beta diversity (as measured by the Bray-Curtis dissimilarity index) were analyzed using standard workflows in QIIME 2-2019.4, with a sampling depth of 1000 reads per sample and default parameters, and downstream statistical analyses were performed using R (http://www.r-project.org/). In brief, differences in alpha and beta diversity between donor and recipient samples were analyzed by Kruskal-Wallis tests or Bonferroni-corrected pairwise Dunn’s tests to compare recipient samples to their respective donor pool. Differences in the proportion of rare and common taxa present in different donor pools were analyzed by pairwise Fisher’s exact tests. Finally, the significant of donor and recipient sample clustering by donor species was analyzed by permutational multivariate analysis of variance (PERMANOVA) implemented in QIIME.

Results

Adult mosquitoes harbor relatively complex bacterial communities that can be isolated for transplantation

For each donor species (Ae. aegypti and Cx. quinquefasciatus), we characterized the microbiota of 40 individual adult mosquitoes by sequencing the V3-V4 regions of the 16S rRNA gene. After filtering, denoising, merging, and removing chimeras, we obtained a total of 2,544,303 reads with a median sequencing depth of 32,803 reads per sample (Additional file 1). We obtained an unusually low number of reads (< 1000) for a single Cx. quinquefasciatus sample (Additional file 1), which was removed from subsequent analyses. We then assigned taxa and plotted relative abundance of taxa across samples.

We identified 103 and 120 ASVs across all of the Ae. aegypti and Cx. quinquefasciatus individuals we sampled, respectively (Additional file 2). However, the vast majority of our sequencing reads (> 90%) were assigned to ASVs belonging to one of four genera: Serratia, Asaia, Cedecea, and another unclassified genus within the Enterobacteriaceae (Fig. 2a; Additional file 2). Considering both the presence/absence and relative abundance of all of the ASVs we detected, bacterial communities present in both donor species exhibited significant differences in both alpha diversity (Fig. 2b; Additional file 1) and beta diversity (Fig. 2c), which were associated with shifts in the relative abundance of specific community members detected in each species (Fig. 2a; Additional file 2). As expected, these included the presence of Wolbachia in Cx. quinquefasciatus donor individuals and the near complete absence of Wolbachia across the Ae. aegypti donor individuals we sampled, which is consistent with no established natural infection ever being observed in this species [28, 30]. Cx. quinquefasciatus donor individuals further contained a notably greater percentage of taxa within the genus Serratia, while Ae. aegypti donor individuals contained a greater percentage of Asaia spp. (Fig. 2a; Additional file 2). Interestingly, we also detected significant negative correlations between the relative abundance of ASVs belonging to the genus Serratia and ASVs belonging to other taxa within the family Enterobacteriaceae across all Ae. aegypti and Cx. quinquefasciatus donors we sampled (Additional files 2 and 3), which is consistent with previous results in field-collected mosquitoes of the same species and our recent experimental findings [58, 63].

Fig. 2
figure 2

a Relative abundance of bacterial genera in individual adult mosquitoes sampled from conventionally maintained populations of each of the donor species used in the study (i.e., Ae. aegypti and Cx. quinquefasciatus). Adults were provided 10% sucrose in water (wt/vol) ad libitum prior to being sampled 3–4 day postemergence. Each bar represents an individual mosquito. Low abundance genera (< 1%) are represented by the ‘Other’ category. b and c Alpha and beta diversity of Ae. aegypti (Aa) and Cx. quinquefasciatus (Cq) donor individuals. Panel b shows the difference in alpha diversity between Ae. aegypti and Cx. quinquefasciatus donor individuals as measured by Shannon’s H index (left) and ASV richness (right). Box-and-whisker plots show high, low, and median values, with lower and upper edges of each box denoting first and third quartiles, respectively. Asterisks (***) indicate significant differences between Ae. aegypti and Cx. quinquefasciatus donor individuals (Kruskal-Wallis test, P < 0.05). Panel c shows the difference in beta diversity between Ae. aegypti and Cx. quinquefasciatus donor individuals. Principal coordinates analysis using the Bray-Curtis dissimilarity index identified significant clustering by donor species (PERMANOVA, P = 0.001)

Full size image

In order to determine how many individuals were required to transfer a representative microbiome to recipients, we generated homogenates using pools of 10, 20, 40, or 80 Ae. aegypti or Cx. quinquefasciatus donor individuals and assessed the diversity of ASVs recovered in each pool relative to ASV diversity across the 40 individuals we previously sequenced from laboratory populations of each donor species (described above). We obtained a total of 438,839 sequences representing 68 and 64 ASVs across the four Ae. aegypti and four Cx. quinquefasciatus donor pools we sequenced, respectively, and each pool was dominated by the same four genera detected in the 40 individuals previously sequenced from each donor species population (Fig. 3a; Additional files 1 and 2). Each pool also captured the majority of donor ASV diversity (> 96%), although recovery varied with respect to how common a given ASV was across all of the donor individuals we sequenced (Fig. 3b; Additional file 2). The number of individuals used to generate each pool had the greatest impact on recovery of rare ASVs (i.e., those present in < 50% of the donor individuals we sequenced), with significantly fewer rare ASVs being recovered in the pool generated using 10 individuals. However, there were no significant differences in recovery of more common ASVs, which were present in ≥ 50% of donor individuals and constituted > 93% of individual donor sequences, between any of the pools we generated (Fig. 3b; Additional file 2).

Fig. 3
figure 3

a Relative abundance of bacterial genera in Ae. aegypti and Cx. quinquefasciatus donor pools. Low abundance genera (< 1%) are represented by the ‘Other’ category. b Proportion of rare ASVs (left) and common ASVs (right) found in at least one donor individual that were present in a given donor pool. An ASV was considered “rare” if it was detected in < 50% of donor individuals, while an ASV was considered “common” if it was detected in ≥ 50% of donor individuals. Pools that do not share a letter above the bars had significantly different results as determined by paired Fisher’s exact tests (P < 0.05); ns, pools not significantly different (P > 0.05)

Full size image

Microbiota transplantation recapitulates donor microbial diversity in recipient individuals

To assess our ability to transplant microbiota between different mosquito species, we introduced each of our Ae. aegypti and Cx. quinquefasciatus donor pools into the water of cultures containing axenic Ae. aegypti larvae. These cultures were subsequently maintained under standard rearing conditions, and 16S rRNA gene amplicon sequencing was used to assess bacterial diversity in replicate samples of the aquatic habitat (water in rearing flasks), larvae (collected as third instars), and adults from each culture (collected 3- and 6-day postemergence). A total of 50, 40, and 108 water, larval, and adult samples were sequenced, respectively, with a total of five samples being discarded prior to downstream analyses due to low sequencing depth (< 1000 reads) (Additional file 1).

The resulting dataset, which contained a total of 4,540,617 sequences across all of the recipient water, larval, and adult samples we sequenced (Additional file 1), revealed that 64 and 61 of the 68 and 64 ASVs found in Ae. aegypti and Cx. quinquefasciatus donor pool communities, respectively, representing > 99% of all donor pool sequences, were detected in recipient samples (Additional file 2). The majority of these ASVs (> 70%) also persisted in recipient communities over time, although there were dramatic shifts in both alpha and beta diversity across the different life stages and water samples we sequenced (Figs. 4 and 5; Additional files 1, 2, 4, and 5). Alpha diversity was overall highest in water and larvae, while adult recipient individuals harbored communities that did not significantly differ in alpha diversity from input donor communities (Fig. 4b; Additional file 1), regardless of the size of the input donor pool (Additional files 1, 4, and 5). Differences in beta diversity, measured as average Bray-Curtis dissimilarity, were also overall higher between input donor communities and the recipient water and larval samples we collected than between input donor communities and recipient adult samples (Fig. 5), although the degree of similarity between recipient adult and input donor communities varied over time postemergence and as a function of the size of the input donor pool (Additional file 6). More specifically, recipient water and larval communities displayed striking amplification of taxa within the Chitinophagaceae, Microbacteriaceae (Leucobacter and Microbacterium spp.), and Flavobacteriaceae (Flavobacterium, Chryseobacterium, and Elizabethkingia spp.) that were less abundant in input donor communities (Fig. 4a; Additional file 2). In contrast, adult recipient communities displayed striking amplification of taxa within the genera Serratia, Asaia, Cedecea, and an unclassified genus within the Enterobacteriaceae, consistent with input donor communities (Fig. 4a; Additional file 2).

Fig. 4
figure 4

a Relative abundance of bacterial genera in donor pools and recipient samples. Biological replicates were pooled for the bar graphs presented. Low abundance genera (< 1%) are represented by the ‘Other’ category. b Alpha diversity of donor pools and recipient samples, as measured by Shannon’s H index and ASV richness. Box-and-whisker plots show high, low, and median values, with lower and upper edges of each box denoted first and third quartiles, respectively. Asterisks (***) indicate samples that significantly differed from the donor pools (Dunn’s test with Bonferroni correction, P < 0.0125)

Full size image
Fig. 5
figure 5

a Principal coordinates analysis using the Bray-Curtis dissimilarity index. Circles are colored by sample source (donor pools, orange; water, purple; larvae, green; 3-day-old adults, blue; 6-day-old adults, red). b Average Bray-Curtis dissimilarity between (b/w) donor pools versus between a given donor pool and recipient samples. Mean values ± standard errors are shown. Asterisks (***) indicate comparisons for which the average dissimilarity between a given donor pool and group of recipient samples was significantly higher than that expected as a result of the transplantation procedure itself (i.e., between donor pools) (Dunn’s test with Bonferroni correction, P < 0.0125)

Full size image

Both host and environmental factors impact microbiota transplantation efficacy

To assess whether microbiota transplantation recapitulated observed differences in microbiota diversity between donor species in recipient individuals, we last compared alpha and beta diversity of donor Ae. aegypti and Cx. quinquefasciatus individuals to recipient Ae. aegypti adults emerging from cultures inoculated with pools generated from each donor species. Consistent with our previous results comparing bacterial communities in donor individuals of each species (Fig. 2), communities in recipient adults that emerged from cultures inoculated with pools generated from each donor species exhibited significant differences in both alpha diversity (Fig. 6b) and beta diversity (Fig. 6c). However, these differences were associated with shifts in the relative abundance of community members that were relatively rare in input donor communities (e.g., taxa within the genera Elizabethkingia, Acinetobacter, Pseudomonas, and Stenotrophomonas) (Figs. 2 and 6a; Additional file 2). More specifically, the predominance of Asaia in Ae. aegypti donor communities was not observed in recipient individuals, likely owing to the inability of this bacterium to reliably persist in the water of larval cultures (Fig. 6a and Additional file 2). Wolbachia from Cx. quinquefasciatus donor communities did not infect recipient individuals (Fig. 6a and Additional file 2), although this was expected given that transfections of Wolbachia into mosquitoes require access through the germline. While these patterns were generally similar between groups of recipient individuals inoculated with input donor pools generated using different quantities of mosquitoes, adult recipients inoculated with pools generated using fewer individuals exhibited more variable bacterial communities overall, due to the stochastic proliferation of rare donor taxa and/or antagonism of Serratia by Enterobacteriaceae, consistent with our previous observations across donor individuals (Fig. 6a; Additional files 2 and 7).

Fig. 6
figure 6

a Relative abundance of bacterial genera in 3-day and 6-day-old Ae. aegypti recipient adults that emerged from cultures inoculated with donor pools generated from either Ae. aegypti or Cx. quinquefasciatus individuals. Each bar represents an individual mosquito. Genera representing > 1% of reads from any one donor individual are listed in the legend; all other taxa are grouped together under “Other.” b and c Alpha and beta diversity of recipient Ae. aegypti adults emerging from cultures inoculated with pools generated from Ae. aegypti (Aa) or Cx. quinquefasciatus (Cq) donor individuals. Panel b shows the difference in alpha diversity between Aa and Cq recipient adults as measured by Shannon’s H index (left) and ASV richness (right). Box-and-whisker plots show high, low, and median values, with lower and upper edges of each box denoting first and third quartiles, respectively. Asterisks (***) indicate significant differences between Aa and Cq recipient adults (Kruskal-Wallis test, P < 0.05). Panel c shows the difference in beta diversity between Aa and Cq recipient adults. Principal coordinates analysis using the Bray-Curtis dissimilarity index identified significant clustering by donor species (PERMANOVA, P = 0.001)

Full size image

Discussion

Numerous studies describing the diversity and function of mosquito-associated microbial taxa and assemblages have been published recently, leading to the discovery of potential interactions between mosquitoes and their microbiota that could be manipulated to enhance or reduce mosquito fitness and/or vector competency (reviewed in [42]). However, questions remain about the reproducibility, applicability, and physiological relevance of these data owing to discrepancies in experimental technique, lack of standardization, and the use of laboratory-colonized mosquito strains and species that harbor microbiota that vary substantially within and between different laboratories and that differ substantially from naturally occurring mosquitoes in the field [12, 13, 73,74,75,76,77,78]. In this study, we developed a simple approach to successfully isolate donor microbial communities from adult mosquitoes. We then used this approach to transfer microbiota within (i.e., Ae. aegypti donors to Ae. aegypti recipients) and between (i.e., Cx. quinquefasciatus donors to Ae. aegypti recipients) different donor and recipient species in order to assess our ability to recapitulate donor microbial diversity in adult recipients.

Our results demonstrate the successful transfer of bacteria from donor to recipient populations of mosquitoes, with recipient adult individuals retaining the vast majority of donor bacterial diversity. Our results also demonstrate that relatively small pools of donor microbiota (i.e., derived from ≥ 10 donor individuals) are sufficient to capture taxa that are highly abundant and/or common in a given donor mosquito population. This suggests that our methods could readily be applied to study microbiota isolated from field populations, even in cases where large-scale mosquito collections are difficult. However, future work will be necessary to confirm that the patterns observed using our approach are indeed the same for donor microbiota generated from field mosquitoes that harbor microbial communities that are more diverse than those present in laboratory mosquitoes and that are not adapted to the laboratory environment [12, 13, 73,74,75,76,77,78]. Recently developed methods to generate axenic adults [34, 59,60,61] also strongly position us to examine the potential to adapt our protocol to introduce field-derived donor microbiota pools directly into adults via a sugar meal and therefore avoiding selective pressures exerted on introduced microbes by standard laboratory larval diets and larval growth and molting.

These results also highlight the value of our approach for studying the underlying bases of mosquito-microbe interactions, as has been demonstrated in other animals. For example, microbiome transplantation approaches have been employed in Nasonia wasps to assess the selective pressures contributing to observed patterns of phylosymbiosis in the system [47] as well as Drosophila melanogaster flies and Bombus terrestris bumblebees to identify relationships between host microbiota composition and different thermotolerance or immunity phenotypes [45, 46]. Reciprocal microbiome transplantations have also been performed across different vertebrate animal species. For example, reciprocal microbiota transplantations between zebrafish and mice have revealed factors specific to the host gut habitat that shape microbial community structure in each species [44]. Indeed, our results point to both host and environmental factors in shaping microbiota acquisition and persistence in mosquitoes. That the microbiota in recipient adult individuals looked most similar to the microbiota of donor individuals supports previous studies in Ae. aegypti identifying life stage as a dominant factor shaping mosquito microbiota [10, 11, 14, 73, 74, 79,80,81,82,83,84]. Additionally, there were differences in microbiota diversity between our donor species in recipient adults which support previous findings indicating that while community membership may be largely driven by the environment and life stage, community features such as total and taxon-specific abundances may also be shaped by host genetics [85, 86]. Future studies could employ microbiome transplantation to improve our understanding of the factors shaping microbiome acquisition and assembly in mosquitoes and the mechanisms by which specific microbial taxa and assemblages contribute to different mosquito traits under controlled conditions.

Future work is also warranted to determine if the approach developed herein is relevant for other microbes such as fungi or viruses, which are also known to impact mosquito biology [87, 88]. The applicability of this approach for other microbes likely depends on their biology and, in particular, their mode of transmission. For example, extracellular members of the mosquito gut microbiota that are commonly detected in environments where mosquitoes persist in the laboratory are likely to be transferred, while those that are intracellular may not be. In line with this, our results supported the expectation that the intracellular bacterium Wolbachia, which was present in the Cx. quinquefasciatus donors used in this study, would not be successfully transferred to Ae. aegypti recipients. We also appreciate that tissue localization of bacteria and other microbes may be pertinent for the transplantation process, and that future studies should integrate complementary approaches to verify the viability of key members of the donor microbiota in recipient individuals’ posttransplantation. Here, we prepared donor microbiota from whole-body mosquitoes and similarly assessed microbiota assembly and persistence in whole-body recipient individuals. Additional work will be necessary to establish patterns of donor microbiota colonization across recipient host tissues and/or to validate methods for isolation of microbiota from specific donor and recipient tissues. Methods for long-term preservation of donor microbiota will also be necessary to facilitate long-term studies and intra- and interlaboratory comparisons of microbiota assembly across different host strains. Nevertheless, our results provide a critical first step toward the standardization of microbiome studies in the field of vector biology to include mosquito hosts colonized by defined microbiota that can be replicated within and between labs. They also provide a critical first step toward our ability to recapitulate and study field-derived microbiota in laboratory settings.

Conclusions

We have successfully isolated and transplanted microbiomes from donor to recipient mosquitoes. This approach lays the foundation for future work to facilitate standardized studies of mosquito-microbe interactions, to examine host-microbe interactions, and to identify effective strategies for manipulating mosquito microbiota to control mosquito populations and mosquito-borne diseases.

Availability of data and materials

Raw Illumina reads are available in the NCBI Sequence Read Archive (http://www.ncbi.nlm.nih.gov/sra) under BioProject ID PRJNA767109. Input files for the QIIME pipeline as well as raw data files and R code for statistical analyses have been deposited in the Dryad Digital Repository: (https://doi.org/10.5061/dryad.5qfttdz7m).

References

  1. Kohl KD, Weiss RB, Cox J, Dale C, Dearing MD. Gut microbes of mammalian herbivores facilitate intake of plant toxins. Ecol Lett. 2014;17:1238–46.

    Article  PubMed  Google Scholar 

  2. Chevalier C, Stojanović O, Colin DJ, Suarez-Zamorano N, Tarallo V, Veyrat-Durebex C, et al. Gut microbiota orchestrates energy homeostasis during cold. Cell. 2015;163:1360–74.

    Article  CAS  PubMed  Google Scholar 

  3. Sommer F, Ståhlman M, Ilkayeva O, Arnemo JM, Kindberg J, Josefsson J, et al. The gut microbiota modulates energy metabolism in the hibernating brown bear Ursus arctos. Cell Rep. 2016;14:1655–61.

    Article  CAS  PubMed  Google Scholar 

  4. Lee STM, Kahn SA, Delmont TO, Shaiber A, Esen ÖC, Hubert NA, et al. Tracking microbial colonization in fecal microbiota transplantation experiments via genome-resolved metagenomics. Microbiome. 2017;5:50.

    Article  PubMed  PubMed Central  Google Scholar 

  5. Hu J, Chen L, Tang Y, Xie C, Xu B, Shi M, et al. Standardized preparation for fecal microbiota transplantation in pigs. Front Microbiol. 2018;9:1328.

    Article  PubMed  PubMed Central  Google Scholar 

  6. Blyton MDJ, Soo RM, Whisson D, Marsh KJ, Pascoe J, Le Pla M, et al. Faecal inoculations alter the gastrointestinal microbiome and allow dietary expansion in a wild specialist herbivore, the koala. Animal Microbiome. 2019;1:6.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Clements AN. The biology of mosquitoes, volume 1: development, nutrition, and reproduction. New York: Chapman & Hall; 1992.

    Google Scholar 

  8. Foster WA. Mosquito sugar feeding and reproductive energetics. Ann Rev Entomol. 1995;40:443–74.

    Article  CAS  Google Scholar 

  9. Vogel KJ, Coon KL. Functions and mechanisms of symbionts of insect disease vectors. In: Oliver KM, Russell JA, editors. Advances in Insect Physiology, vol. 58. London: Academic Press; 2020. p. 233–75.

    Google Scholar 

  10. Coon KL, Vogel KJ, Brown MR, Strand MR. Mosquitoes rely on their gut microbiota for development. Mol Ecol. 2014;23:2727–39.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  11. Gimonneau G, Tchioffo MT, Abate L, Boissiere A, Awono-Ambene PH, Nsango SE, et al. Composition of Anopheles coluzzii and Anopheles gambiae microbiota from larval to adult stages. Infect Genet Evol. 2014;28:715–24.

    Article  PubMed  Google Scholar 

  12. Coon KL, Brown MR, Strand MR. Mosquitoes host communities of bacteria that are essential for development but vary greatly between local habitats. Mol Ecol. 2016;25:5806–26.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  13. Bascuñán P, Niño-Garcia JP, Galeano-Castañeda Y, Serre D, Correa MM. Factors shaping the gut bacterial community assembly in two main Colombian malaria vectors. Microbiome. 2018;6:148.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Wang Z, Liu T, Wu Y, Zhong D, Zhou G, Su Z, et al. Bacterial microbiota assemblage in Aedes albopictus mosquitoes and its impacts on larval development. Mol Ecol. 2018;27:2972–85.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Moll RM, Romoser WS, Modrzakowski MC, Moncayo AC, Lerdthusnee K. Meconial peritrophic membranes and the fate of midgut bacteria during mosquito (Diptera: Culicidae) metamorphosis. J Med Entomol. 2001;38:29–32.

    Article  CAS  PubMed  Google Scholar 

  16. Moncayo A, Lerdthusnee K, Leon R, Robich R, Romoser W. Meconial peritrophic matrix structure, formation, and meconial degeneration in mosquito pupae/pharate adults: histological and ultrastructural aspects. J Med Entomol. 2005;42:939–44.

    Article  PubMed  Google Scholar 

  17. Briegel H. Physiological bases of mosquito ecology. J Vector Ecol. 2003;28:1–11.

    PubMed  Google Scholar 

  18. Walker ED, Olds EJ, Merritt RW. Gut content analysis of mosquito larvae (Diptera: Culicidae) using DAPI stain and epifluorescence microscopy. J Med Entomol. 1988;25:551–4.

    Article  CAS  PubMed  Google Scholar 

  19. Merritt RW, Olds EJ, Walker ED. Natural food and feeding ecology of larval Coquillettida perturbans. J Am Mosq Control Assoc. 1990;6:35–42.

    CAS  PubMed  Google Scholar 

  20. Gusmão D, Santos A, Marini D, Bacci M, Berbert-Molina M, Lemos F. Culture dependent and culture-independent characterization of microorganisms associated with Aedes aegypti (Diptera: Culicidae) (L.) and dynamics of bacterial colonization in the midgut. Acta Trop. 2010;115:275–81.

    Article  PubMed  Google Scholar 

  21. Vogel KJ, Valzania L, Coon KL, Brown MR, Strand MR. Transcriptome sequencing reveals large-scale changes in axenic Aedes aegypti larvae. PLoS Negl Trop Dis. 2017;11:e0005273.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  22. Favia G, Ricci I, Damiani C, Raddadi N, Crotti E, Marzorati M, et al. Bacteria of the genus Asaia stably associate with Anopheles stephensi, an Asian malarial mosquito vector. Proc Natl Acad Sci USA. 2007;104:9047–51.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Damiani C, Ricci I, Crotti E, Rossi P, Rizzi A, Scuppa P, et al. Paternal transmission of symbiotic bacteria in malaria vectors. Curr Biol. 2008;18:R1087–8.

    Article  CAS  PubMed  Google Scholar 

  24. Crotti E, Damiani C, Pajoro M, Gonella E, Rizzi A, Ricci I, et al. Asaia, a versatile acetic acid bacterial symbiont, capable of cross-colonizing insects of phylogenetically-distant genera and orders. Environ Microbiol. 2009;11:3252–64.

    Article  CAS  PubMed  Google Scholar 

  25. Wang S, Dos-Santos ALA, Huang W, Liu KC, Oshaghi MA, Wei G, et al. Driving mosquito refractoriness to Plasmodium falciparum with engineered symbiotic bacteria. Science. 2017;357:1399–402.

    Article  CAS  PubMed  Google Scholar 

  26. Yen JH. Transovarial transmission of Rickettsia-like microorganisms in mosquitoes. Ann N Y Acad Sci. 1975;266:152–61.

    Article  CAS  PubMed  Google Scholar 

  27. De Almeida F, Moura AS, Cardoso AF, Winter CE, Bijovsky AT, Suesdek L. Effects of Wolbachia on fitness of Culex quinquefasciatus (Diptera; Culicidae). Infect Genet Evol. 2011;11:2138–43.

    Article  PubMed  Google Scholar 

  28. Gloria-Soria A, Chiodo TG, Powell JR. Lack of evidence for natural Wolbachia infections in Aedes aegypti (Diptera: Culicidae). J Med Entomol. 2018;55:1354–6.

    PubMed  PubMed Central  Google Scholar 

  29. Ant TH, Herd C, Louis F, Failloux AB, Sinkins SP. Wolbachia transinfections in Culex quinquefasciatus generate cytoplasmic incompatibility. Insect Mol Biol. 2020;29:1–8.

    Article  CAS  PubMed  Google Scholar 

  30. Ross PA, Callahan AG, Yang Q, Jasper M, Arif MAK, Afizah AN, et al. An elusive endosymbiont: does Wolbachia occur naturally in Aedes aegypti? Ecol Evol. 2020;10:1581–91.

    Article  PubMed  PubMed Central  Google Scholar 

  31. Walker T, Quek S, Jeffries CL, Bandibabone J, Dhokiya V, Bamou R, et al. Stable high-density and maternally inherited Wolbachia infections in Anopheles moucheti and Anopheles demeilloni mosquitoes. Curr Biol. 2021;31:2310–20.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Quek S, Cerderia L, Jeffries CL, Tomlinson S, Walker T, Hughes GL, et al. Wolbachia endosymbionts in two Anopheles species indicates independent acquisitions and lack of prophage elements. bioRxiv. 2021. https://doi.org/10.1101/2021.11.15.468614.

  33. Coon KL, Brown MR, Strand MR. Gut bacteria differentially affect egg production in the anautogenous mosquito Aedes aegypti and facultatively autogenous mosquito Aedes atropalpus (Diptera: Culicidae). Parasit Vectors. 2016;9:1–12.

    Article  CAS  Google Scholar 

  34. Valzania L, Martinson VG, Harrison RE, Boyd BM, Coon KL, Brown MR, et al. Both living bacteria and eukaryotes in the mosquito gut promote growth of larvae. PLoS Negl Trop Dis. 2018;12:e0006638.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  35. Wang Y, Eum JH, Harrison RE, Valzania L, Yang X, Johnson JA, et al. Riboflavin instability is a key factor underlying the requirement of a gut microbiota for mosquito development. Proc Natl Acad Sci USA. 2021;118:e2101080118.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  36. Ramirez JL, Short SM, Bahia AC, Saraiva RG, Dong Y, Kang S, et al. Chromobacterium Csp_P reduces malaria and dengue infection in vector mosquitoes and has entomopathogenic and in vitro anti-pathogen activities. PLoS Pathog. 2014;23:e1004398.

    Article  CAS  Google Scholar 

  37. Wei G, Lai Y, Wang G, Chen H, Li F, Wang S. Insect pathogenic fungus interacts with the gut microbiota to accelerate mosquito mortality. Proc Natl Acad Sci USA. 2017;114:5994–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  38. Dada N, Sheth M, Liebman K, Pinto J, Lenhart A. Whole metagenome sequencing reveals links between mosquito microbiota and insecticide resistance in malaria vectors. Sc Rep. 2018;8:2084.

    Article  CAS  Google Scholar 

  39. Gaio AD, Gusmão DS, Santos AV, Berbert-Molina MA, Pimenta PFP, Lemos FJA. Contribution of midgut bacteria to blood digestion and egg production in Aedes aegypti (Diptera: Culicidae) (L.). Parasit Vectors. 2011;4:105.

    Article  PubMed Central  Google Scholar 

  40. Hegde S, Rasgon JL, Hughes GL. The microbiome modulates arbovirus transmission in mosquitoes. Curr Opin Virol. 2015;15:97–102.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  41. Saldaña MA, Hegde S, Hughes GL. Microbial control of arthropod-borne disease. Mem Inst Oswaldo Cruz. 2017;112:81–93.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  42. Cansado-Utrilla C, Zhao SY, McCall PJ, Coon KL, Hughes GL. The microbiome and mosquito vectorial capacity: rich potential for discovery and translation. Microbiome. 2021;9:111.

    Article  PubMed  PubMed Central  Google Scholar 

  43. Huang W, Wang S, Jacobs-Lorena M. Use of microbiota to fight mosquito-borne disease. Front Genet. 2020;11:196.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  44. Rawls JF, Mahowald MA, Ley RE, Gordon JI. Reciprocal gut microbiota transplants from zebrafish and mice to germ-free recipients reveal host habitat selection. Cell. 2006;127:423–33.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  45. Näpflin K, Schmid-Hempel P. Immune response and gut microbial community structure in bumblebees after microbiota transplants. Proc Biol Sci. 2016;283:20160312–8.

    PubMed  PubMed Central  Google Scholar 

  46. Moghadam NN, Thorshauge PM, Kristensen TN, de Jonge N, Bahrndorff S, Kjeldal H, et al. Strong responses of Drosophila melanogaster microbiota to developmental temperature. Fly. 2018;12:1–12.

    Article  PubMed  Google Scholar 

  47. Van Opstal EJ, Bordenstein SR. Phylosymbiosis impacts adaptive traits in Nasonia wasps. mBio. 2019;10:e00887–19.

    PubMed  PubMed Central  Google Scholar 

  48. Song X, Wang M, Zhu H, Wang J. PGRP-LD mediates A. stephensi vector competency by regulating homeostasis of microbiota-induced peritrophic matrix synthesis. PLoS Pathog. 2018;14:e1006899.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  49. Bai L, Wang L, Vega-Rodríguez J, Wang G, Wang S. A gut symbiotic bacterium Serratia marcescens renders mosquito resistance to Plasmodium infection through activation of mosquito immune responses. Front Microbiol. 2019;10:1580.

    Article  PubMed  PubMed Central  Google Scholar 

  50. Wu P, Sun P, Nie K, Zhu Y, Shi M, Xiao C, et al. A gut commensal bacterium promotes permissiveness to arboviruses. Cell Host Microbe. 2019;25:101–12.

    Article  CAS  PubMed  Google Scholar 

  51. Gendrin M, Rodgers FH, Yerbanga RS, Ouédraogo JB, Basáñez MG, Cohuet A, et al. Antibiotics in ingested human blood affect the mosquito microbiota and capacity to transmit malaria. Nat Commun. 2015;6:5921.

    Article  PubMed  Google Scholar 

  52. Ballard JWO, Melvin RG. Tetracycline treatment influences mitochondrial metabolism and mtDNA density two generations after treatment in Drosophila. Insect Mol Biol. 2007;16:799–802.

    Article  CAS  PubMed  Google Scholar 

  53. Ridley EV, Wong CAN, Douglas AE. Microbe-dependent and nonspecific effects of procedures to eliminate the resident microbiota from Drosophila melanogaster. Appl Environ Microbiol. 2013;79:3209–14.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  54. Moullan N, Mouchiroud L, Wang X, Ryu D, Williams EG, Mottis A, et al. Tetracyclines disturb mitochondrial function across eukaryotic models: a call for caution in biomedical research. Cell Rep. 2015;10:1681–91.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  55. Chabanol E, Behrends V, Prévot G, Christophides GK, Gendrin M. Antibiotic treatment in Anopheles coluzzii affects carbon and nitrogen metabolism. Pathogens. 2020;9:679.

    Article  CAS  PubMed Central  Google Scholar 

  56. Chouaia B, Rossi P, Epis S, Mosca M, Ricci I, Damiani C, et al. Delayed larval development in Anopheles mosquitoes deprived of Asaia bacterial symbionts. BMC Microbiol. 2012;12:S2.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  57. Bahia AC, Dong Y, Blumberg BJ, Mlambo G, Tripathi A, BenMarzouk-Hidalgo OJ, et al. Exploring Anopheles gut bacteria for Plasmodium blocking activity. Environ Microbiol. 2014;16:2980–94.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  58. Kozlova EV, Hegde S, Roundy CM, Golovko G, Saldaña MA, Hart CE, et al. Microbial interactions in the mosquito gut determine Serratia colonization and blood feeding propensity. ISME J. 2020;15:93–108.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  59. Munderloh UG, Kurtti TJ, Maramorosch K. Anopheles stephensi and Toxorhynchites amboinensis: aseptic rearing of mosquito larvae on cultured cells. J Parasitol. 1982;68:1085–91.

    Article  CAS  PubMed  Google Scholar 

  60. Correa MA, Matusovsky B, Brackney DE, Steven B. Generation of axenic Aedes aegypti demonstrate live bacteria are not required for mosquito development. Nat Comm. 2018;9:R37.

    Article  CAS  Google Scholar 

  61. Romoli O, Schönbeck JC, Hapfelmeier S, Gendrin M. Production of germ-free mosquitoes via transient colonisation allows stage-specific investigation of host microbiota interactions. Nature Comm. 2021;12:942.

    Article  CAS  Google Scholar 

  62. Coon KL, Valzania L, McKinney DA, Vogel KJ, Brown MR, Strand MR. Bacteria mediated hypoxia functions as a signal for mosquito development. Proc Natl Acad Sci USA. 2017;114:E5362–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  63. Hegde S, Khanipov K, Albayrak L, Golovko G, Pimenova M, Saldaña MA, et al. Microbiome interaction networks and community structure from laboratory-reared and field-collected Aedes aegypti, Aedes albopictus, and Culex quinquefasciatus mosquito vectors. Front Microbiol. 2018;9:715.

    Article  Google Scholar 

  64. Valzania L, Coon KL, Vogel KJ, Brown MR, Strand MR. Hypoxia-induced transcription factor signaling is essential for larval growth of the mosquito Aedes aegypti. Proc Natl Acad Sci USA. 2018;115:457–65.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  65. Herlemann DPR, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571–9.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  66. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet CC, Al-Ghalith GA, et al. Reproducible, interactive, scalable and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;37:852–7.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  67. Callahan BJ, McMurdie PJ, Rosen MJ, Han AW, Johnson AJA, Holmes SP. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  68. McDonald D, Prince MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, et al. An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J. 2011;6:610–8.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  69. Werner JJ, Koren O, Hugenholtz P, DeSantis TZ, Walters WA, Caporaso JG, et al. Impact of training sets on classification of high throughput bacterial 16S rRNA gene surveys. ISME J. 2012;6:94–103.

    Article  CAS  PubMed  Google Scholar 

  70. Price MN, Dehal PS, Arkin AP. FastTree 2 – approximately maximum-likelihood trees for large alignments. PLoS One. 2010;5:e9490.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  71. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30:772–80.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  72. DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol. 2006;72:5069–72.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  73. Zouache K, Raharimalala FN, Raquin V, Tran-Van V, Raveloson LHR, Ravelonandro P, et al. Bacterial diversity of field-caught mosquitoes, Aedes albopictus and Aedes aegypti, from different geographic regions of Madagascar. FEMS Microbiol Ecol. 2011;75:377–89.

    Article  CAS  PubMed  Google Scholar 

  74. Boissière A, Tchioffo MT, Bachar D, Abate L, Marie A, Nsango SE, et al. Midgut microbiota of the malaria mosquito vector Anopheles gambiae and interactions with Plasmodium falciparum infection. PLoS Pathog. 2012;8:e1002742.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  75. Buck M, Nilsson LK, Brunius C, Dabire RK, Hopkins R, Terenius O. Bacterial associations reveal spatial population dynamics in Anopheles gambiae mosquitoes. Sci Rep. 2016;10:22806.

    Article  CAS  Google Scholar 

  76. Muturi EJ, Lagos-Kutz D, Dunlap C, Ramirez JL, Rooney AP, Hartman GL. Mosquito microbiota cluster by host sampling location. Parasit Vectors. 2018;11:468.

    Article  PubMed  PubMed Central  Google Scholar 

  77. Tchioffo MT, Boissière A, Abate L, Nsango SE, Bayibéki AN, Awono-Ambéné PH, et al. Dynamics of bacterial community composition in the malaria mosquito’s epithelia. Front Microbiol. 2016;5:1500.

    Google Scholar 

  78. Dickson LB, Ghozlane A, Volant S, Bouchier C, Ma L, Vega-Rúa A, et al. Diverse laboratory colonies of Aedes aegypti harbor the same adult midgut bacterial microbiome. Parasit Vectors. 2018;11:207.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  79. Wang Y, Gilbreath TM, Kukutla P, Yan G, Xu J. Dynamic gut microbiome across life history of the malaria mosquito Anopheles gambiae in Kenya. PLoS One. 2011;6:e24767.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  80. Osei-Poku J, Mbogo CM, Palmer WJ, Jiggins FM. Deep sequencing reveals extensive variation in the gut microbiota of wild mosquitoes from Kenya. Mol Ecol. 2012;21:5138–50.

    Article  CAS  PubMed  Google Scholar 

  81. Duguma D, Hall MW, Rugman-Jones P, Stouthamer R, Terenius O, Neufeld JD, et al. Developmental succession of the microbiome of Culex mosquitoes. BMC Microbiol. 2015;15:140.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  82. Muturi EJ, Kim C, Bara J, Bach EM, Siddappaji MH. Culex pipiens and Culex restuans mosquitoes harbor distinct microbiota dominated by few bacterial taxa. Parasit Vectors. 2016;9:18.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  83. Muturi EJ, Ramirez JL, Rooney AP, Kim CH. Comparative analysis of gut microbiota of mosquito communities in central Illinois. PLoS Negl Trop Dis. 2017;11:e0005377.

    Article  PubMed  PubMed Central  Google Scholar 

  84. Thongsripong P, Chandler JA, Green AB, Kittyapong P, Wilcox BA, Kapan DD, et al. Mosquito vector-associated microbiota: metabarcoding bacteria and eukaryotic symbionts across habitat types in Thailand endemic for dengue and other arthropod-borne diseases. Ecol Evol. 2017;8:1352–68.

    Article  PubMed  PubMed Central  Google Scholar 

  85. Charan SS, Pawar KD, Severson DW, Patole MS, Shouche YS. Comparative analysis of midgut bacterial communities of Aedes aegypti mosquito strains varying in vector competence to dengue virus. Parasitol Res. 2013;112:2627–37.

    Article  PubMed  Google Scholar 

  86. Short SM, Mongodin EF, MacLeod HJ, Talyuli OAC, Dimopoulos G. Amino acid metabolic signaling influences Aedes aegypti midgut microbiome variability. PLoS Negl Trop Dis. 2017;11:e0005677.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  87. Tawidian P, Rhodes VL, Michel K. Mosquito-fungus interactions and antifungal immunity. Insect Biochem Mol Biol. 2019;111:103182.

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  88. Patterson EI, Villinger J, Muthoni JN, Dobel-Ober L, Hughes GL. Exploiting insect-specific viruses as a novel strategy to control vector-borne disease. Curr Opin Insect Sci. 2020;39:50–6.

    Article  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

We thank George Golovko, Kamil Khanipov, and Maria Pimenova of the Department of Pharmacology and Toxicology, Sealy Center for Structural Biology, University of Texas Medical Branch (Galveston, TX, USA) for assistance with sequencing. We also thank the insectary staff at the University of Texas Medical Branch for assistance in rearing mosquitoes.

Funding

GLH and KLC were supported by an NIH grant (R21AI138074). Additional support to KLC was provided by the NSF (2019368), the USDA NIFA (2018-67012-28009), and the University of Wisconsin-Madison. Additional support to GLH was provided by the NIH (R21AI129507), the BBSRC (BB/T001240/1, V011278/1, and BB/W018446/1), the UKRI (20197 and 85336), the EPSRC (V043811/1), a Royal Society Wolfson Fellowship (RSWF\R1\180013), and the NIHR (NIHR2000907). SH was supported by a James W. McLaughlin postdoctoral fellowship from the University of Texas Medical Branch and a Liverpool School of Tropical Medicine Director’s Catalyst Fund award. The views expressed herein are those of the author(s) and do not necessarily reflect those of any agency of the US or UK government.

Author information

Author notes

  1. Kerri L. Coon and Shivanand Hegde contributed equally to this work.

Authors and Affiliations

  1. Department of Bacteriology, University of Wisconsin-Madison, Madison, WI, 53706, USA

    Kerri L. Coon

  2. Departments of Vector Biology and Tropical Disease Biology, Centre for Neglected Topical Disease, Liverpool School of Tropical Medicine, Liverpool, L3 5QA, UK

    Shivanand Hegde & Grant L. Hughes

Authors
  1. Kerri L. Coon
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Shivanand Hegde
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Grant L. Hughes
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

KLC, SH, and GLH conceived and designed the experiments. SH performed the experiments. KLC carried out the data analysis. KLC wrote the initial manuscript, and SH and GLH contributed to revisions. The authors read and approved the final manuscript.

Corresponding authors

Correspondence to Kerri L. Coon or Grant L. Hughes.

Ethics declarations

Ethics approval and consent to participate

Not applicable.

Consent for publication

Not applicable.

Competing interests

The authors declare that they have no competing interests.

Additional information

Publisher’s Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Additional file 1: Supplementary Table 1.

Sequencing and diversity statistics for 16S rRNA gene amplicon libraries prepared from donor and recipient samples.

Additional file 2: Supplementary Table 2.

Taxonomic assignments and prevalence of each ASV in each sample, along with whether a particular ASV was considered ‘rare’ or ‘common’ among individuals of a particular donor species.

Additional file 3: Supplementary Figure 1.

Significantly negative correlation between relative abundance of ASVs belonging to the bacterial family Enterobacteriaceae and ASVs belonging to the genus Serratia across all Ae. aegypti and Cx. quinquefasciatus donor individuals (Spearman’s rank test, P < 0.05).

Additional file 4: Supplementary Figure 2.

(Left) Relative abundance of bacterial genera in Ae. aegypti donor pools and recipient samples. Biological replicates were pooled for the bar graphs presented. Low abundance genera (<1%) are represented by the ‘Other’ category. (Right) Alpha diversity of donor pools and recipient samples, as measured by Shannon’s H index and ASV richness. Box-and-whisker plots show high, low, and median values, with lower and upper edges of each box denoting first and third quartiles, respectively. Asterisks (***) indicate samples that significantly differed from the donor pools (Dunn’s test with Bonferroni correction, P < 0.0125).

Additional file 5: Supplementary Figure 3.

(Left) Relative abundance of bacterial genera in Cx. quinquefasciatus donor pools and recipient samples. Biological replicates were pooled for the bar graphs presented. Low abundance genera (<1%) are represented by the ‘Other’ category. (Right) Alpha diversity of donor pools and recipient samples, as measured by Shannon’s H index and ASV richness. Box-and-whisker plots show high, low, and median values, with lower and upper edges of each box denoting first and third quartiles, respectively. Asterisks (***) indicate samples that significantly differed from the donor pools (Dunn’s test with Bonferroni correction, P < 0.0125).

Additional file 6: Supplementary Figure 4.

Average Bray-Curtis dissimilarity between (b/w) donor pools versus between a given donor pool and recipient samples. Mean values ± standard errors are shown. Asterisks (***) indicate comparisons for which the average dissimilarity between a given donor pool and group of recipient samples was significantly higher than that expected as a result of the transplantation procedure itself (i.e., between donor pools) (Dunn’s test with Bonferroni correction, P < 0.0125).

Additional file 7: Supplementary Figure 5.

Significantly negative correlation between relative abundance of ASVs belonging to the bacterial family Enterobacteriaceae and ASVs belonging to the genus Serratia across all recipient Ae. aegypti adults (Spearman’s rank test, P < 0.05).

Rights and permissions

Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Coon, K.L., Hegde, S. & Hughes, G.L. Interspecies microbiome transplantation recapitulates microbial acquisition in mosquitoes. Microbiome 10, 58 (2022). https://doi.org/10.1186/s40168-022-01256-5

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1186/s40168-022-01256-5

Keywords

Microbiome

ISSN: 2049-2618

Contact us