Adaptive Sequencing Resolves Bacterial Genomes from the Mosquito Microbiome: Linking Function to Larval Development

ABSTRACT Adaptive sequencing was employed as a host DNA depletion approach to improve microbial sequence recovery from Aedes aegypti larvae. This methodology was applied to a colonization experiment where axenic larvae were reared in water collected from three habitats allowing for microbial colonization. Both cultivation and adaptive sequencing were pursued to characterize the microbiomes. Culturing bacteria facilitated the enumeration of larval-associated bacteria, and whole-genome sequencing of representative isolates provided reference genomes for the validation of metagenome assembled genome (MAG) reconstruction. Cultivation and read abundance in the metagenomes both recapitulated unique bacterial populations among larvae exposed to the three environments, highlighting the utility of the method for ecologically informed metagenomics. Assembly of sequence reads recovered three high-quality MAGs (completeness >90%). Two MAGs shared >99% sequence identity to genomes of cultured isolates, validating the robustness of assemblies. Comparative analysis of Comamonas and Bacillus genomes, dominant taxa within the larval microbiome, revealed extensive intra-genus functional redundancy, with over 80% of identified functional orthologs conserved across all analyzed genomes. Yet, gnotobiotic larvae colonized with isolated strains revealed significant phenotypic divergence. For instance, one Comamonas isolate was largely lethal to larvae, while another supported development comparable to a conventional microbiome. Collectively, these findings validate adaptive sequencing as a tool for host-associated metagenomics, facilitating the recovery of high-quality genomes, paired with functional validation within a controlled gnotobiotic mosquito experimental system. These coupled methods allow for the differentiation between conserved genetic elements presumably required for larval colonization versus lineage-specific genes that may drive phenotypic heterogeneity within the host.