Search bioRxiv⌕ Search

bioRxiv · 10.1101/2025.05.27.656271

Bacterial Community Structure and Diversity of Common Mosquito Species in Chengdu: Insights from PacBio Third-Generation

Abstract

Mosquitoes, as critical vectors of diseases such as Japanese encephalitis, dengue fever, and yellow fever, pose significant public health risks in Chengdu, a subtropical city in southwestern China. This study integrated ecological surveillance and PacBio third-generation sequencing to characterize the symbiotic microbiota of four dominant mosquito species (Aedes albopictus, Culex pipiens, Culex tritaeniorhynchus, and Armigeres subalbatus) across urban and rural habitats. From 2020 to 2024, mosquito density monitoring revealed spatial heterogeneity(Aedes albopictus, Culex pipiens, Culex tritaeniorhynchus, and Anopheles sinensis), with outer ring areas exhibiting the highest density (34.69 mosquitoes per trap), while central urban zones had the lowest (3.60). Sequencing identified 717 high-quality Amplicon Sequence Variants (ASVs), with Aedes albopictus harboring the most unique bacterial species (191). Beta diversity analysis demonstrated distinct microbial clustering among species, driven by Pseudomonadota dominance (54.27-93.89%) and variations in secondary phyla (Bacteroidota, Campylobacterota). Functional prediction via KEGG highlighted elevated human disease-associated pathways in Ae. albopictus, contrasting with reduced environmental adaptation activity. Notably, Wolbachia (clade B) and Klebsiella variicola exhibited species-specific abundance patterns, underscoring their roles in pathogen suppression and public health risks. Unclassified taxa (norank_d Bacteria, Candidatus_Hydrogenedentes) clustered near novel mosquito-associated spirochetes, suggesting underexplored functional microbiota. This study provides foundational data for understanding mosquito-microbe interactions and informs strategies for mitigating vector-borne disease. Author SummaryMosquito-borne diseases such as dengue fever and Japanese encephalitis pose severe public health risks in subtropical regions, yet critical gaps remain in understanding how mosquito-associated microbes influence disease transmission in under-resourced areas. Chengdu, a megacity in southwestern China, faces unique challenges due to rapid urbanization, climatic suitability for mosquito proliferation, and disparities in public health infrastructure compared to eastern coastal regions. This study integrates five years of ecological surveillance (2020-2024) and PacBio third-generation sequencing to map mosquito density patterns and characterize symbiotic bacterial communities in four dominant mosquito species (Aedes albopictus, Culex pipiens, Culex tritaeniorhynchus, and Armigeres subalbatus). Key findings reveal stark spatial heterogeneity in mosquito density, with rural outer-ring areas harboring 10-fold higher densities (34.69 mosquitoes/trap) than urban centers. Notably, Aedes albopictus exhibited the highest diversity of unique symbiotic bacteria (191 species), including Wolbachia (clade B), known to suppress arboviruses like dengue. Conversely, Armigeres subalbatus carried high abundances of Klebsiella variicola, an emerging human pathogen linked to severe infections. Functional analyses further highlighted elevated human disease-associated pathways in Ae. albopictus, underscoring its dual role as a disease vector and microbial reservoir. This work provides the first comprehensive baseline data on mosquito-microbe interactions in Chengdu, identifying actionable targets for biocontrol (e.g., leveraging Wolbachia) and early-warning systems for pathogen surveillance. By bridging ecological, molecular, and public health perspectives, our findings offer critical insights for mitigating neglected tropical diseases in subtropical regions where socioeconomic disparities intersect with high disease burdens.

Explore related subjects

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

Xing, Y., Wenjia, T., Wei, Z., Zelin, L., Rong, L., Kai, X., Shuangfeng, F.. 2025-05-27. Bacterial Community Structure and Diversity of Common Mosquito Species in Chengdu: Insights from PacBio Third-Generation. https://doi.org/10.1101/2025.05.27.656271

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related preprints

A population-scale landscape of the subgingival microbiome reveals divergent routes to periodontal dysbiosis

Periodontitis is an archetypical mucosal inflammatory disease in which microbiome dysbiosis at the tooth-epithelial interface interacts with host genetic and behavioral risk factors to drive immune-mediated tissue destruction. Although subgingival microbiome compositional shifts are thought to parallel disease severity, microbiome variation at the population-level and its relationship to periodontal clinical phenotypes and disease-modifying factors remain poorly defined. Here, we use unsupervised manifold learning to map the compositional landscape of the subgingival microbiome in 1,355 adults spanning periodontal health to severe periodontitis. We identified eight latent microbiome states organized along a branching continuum from eubiosis to dysbiosis. An intermediate microbial configuration marked ecological destabilization and bifurcation into two distinct periodontitis-associated dysbiotic trajectories, distinguished by links to gingival inflammation and smoking. Although the microbiome trajectories broadly tracked periodontal destruction, a minority of individuals showed discordant microbiome-clinical phenotypes, with some individuals with periodontitis retaining otherwise eubiotic microbiomes enriched for low-abundance pathobionts, while some cases of health or mild disease had highly dysbiotic communities, suggesting distinct host susceptibility. Together, these findings define a population-scale ecological landscape of the subgingival microbiome, reveal divergent trajectories to periodontal dysbiosis, and highlight heterogeneity in the relationship between microbial community structure and clinical disease expression.

microbiology↗

Rapid and largely reversible shifts in the canine fecal metabolome during dietary change

Diet can rapidly change the fecal metabolome, but less is known about recovery after the original diet is restored. We used untargeted UPLC-MS metabolomics to analyze 72 fecal samples from nine Pumi dogs during an owner-managed switch from dry food to raw food and back to dry food. Diet phase accounted for a large proportion of variation in both ionization modes. More than 13,000 LC-MS features changed at the first sampling point after the switch to raw food, with a similarly large response after return to dry food. Among features significant in both comparisons, more than 99% changed in opposite directions. At the final sampling point, no positive-mode (ESI+) features and only 13 negative-mode (ESI-) features differed from the second dry-food baseline under the same threshold. BARF-associated patterns persisted in analyses excluding individual dogs and in pedigree-adjusted candidate models, although individual feature effects depended on normalization. Putative metabolites from several biochemical classes differed in their response and recovery. The fecal metabolome therefore changed rapidly and returned largely toward baseline, with differences among dogs.

microbiology↗

Taxonomic and functional concordance between full-length ONT 16S and ONT shotgun metagenomics in the canine gut microbiome

Background: Full-length Oxford Nanopore Technologies (ONT) 16S rRNA sequencing provides a scalable view of microbial community composition and can support phylogeny-based functional prediction, but it is not equivalent to shotgun metagenomics. We asked which biological conclusions are preserved when the same canine fecal specimens are profiled by full-length ONT 16S and ONT whole-genome shotgun (WGS) sequencing, and how their agreement depends on analytical scale, reference representation and classifier. Methods: Ninety-seven fecal specimens from 51 dogs were profiled with both assays from the same DNA extract. Functional profiles predicted from NanoASV/NanoPredict with PICRUSt2 were compared with WGS-supported KEGG Ortholog (KO) profiles generated by Kadath. Taxonomy was benchmarked in a source-genome-matched RefSeq universe and in a host-specific DogMAG universe using minitax and Kraken2. Agreement was evaluated at whole-profile, feature-abundance, detection, between-sample structure and biological-inference scales. Age-associated transfer was assessed with dog-aware continuous mixed models, grouped signed-score analyses and paired/dog-blocked PERMANOVA. Results: Functional whole-profile concordance was high: median within-sample CLR Spearman correlations ranged from 0.781 to 0.860 across developmental strata, while between-sample functional structure remained significant by Mantel (rho=0.543) and Procrustes (r=0.693; both p=0.001). Feature-wise transfer was substantially weaker (median KO-wise CLR Spearman=0.318). Continuous age-associated KO slopes showed substantial cross-assay concordance (Spearman=0.727; signed-score Spearman=0.753; direction agreement=77.9%), although 1,290/5,258 eligible KOs retained significant assay-by-age interactions. Taxonomically, exact genus/species abundance agreement was much lower than agreement in between-sample ecological structure. Host-specific DogMAG improved species-level median Spearman from 0.261 to 0.656 for minitax SpeciesEstimate and from 0.181 to 0.512 for Kraken2. The classifier effect was independent of reference choice: under both RefSeq and DogMAG, minitax yielded stronger 16S-WGS concordance than Kraken2, with all eight prespecified RefSeq paired genus/species endpoints and all 10 DogMAG primary paired endpoints significant after BH correction. The same ordering extended to developmental inference, with DogMAG genus/species age-slope concordance of 0.795/0.799 for SpeciesEstimate versus 0.693/0.702 for Kraken2. Taxonomic Aitchison PERMANOVA detected age-associated structure in every assay/reference/classifier/rank combination, whereas age-by-assay interactions were consistently significant but small (R2 approximately 1.1 to 2.2%). Stricter NanoASV identity thresholds removed substantial 16S abundance without improving species-level agreement. Conclusions: The extent of cross-assay agreement depends on the level of analysis. Full-length ONT 16S preserves broad functional organization, ecological structure and much of the direction of age-associated change, but exact fine-rank composition, individual-feature abundance and effect magnitude remain assay dependent. Host-specific reference representation substantially narrows the taxonomic gap, and classifier choice exerts an additional independent effect: within the same matched reference set, minitax consistently yields stronger 16S-WGS concordance than Kraken2 across abundance, detection, ecological-distance and developmental-inference endpoints. Full-length ONT 16S is therefore well suited to broad ecological screening and hypothesis generation, whereas WGS remains preferable when conclusions depend on quantitative fine-rank composition, directly supported gene content or precise feature-level effect estimates.

microbiology↗