Causes and consequences of microbiome formation in mosquito larvae

Abstract

The assembly of host‐associated microbial communities is influenced by multiple factors, but the effect of microbiomes on host phenotypes is often not well understood. To address questions of food‐web effects on host microbiome assembly, we manipulated the resource environment (grass only [G] vs. grass + nutrients [GN]), competition type (intra‐ vs. inter‐specific) and density (high vs. low) for Culex restuans mosquito larvae. We predicted the microbial communities in fourth‐instar larvae would differ between these environmental treatments and that these treatments would translate into differences in the adult phenotype. Resource environment and density influenced the larval microbiome. In addition, the larval microbiome exhibited notable differences compared to the free‐living microbial communities. Resource‐driven differences in the larval samples can be attributed to Arcobacteraceae being more abundant in larvae reared in the GN treatments relative to those reared in the G treatments and Comamonadaceae being more abundant in the G treatment. Although significant, the difference in community structure between density treatments was difficult to discern. This appears to be driven by Weeksellaceae only being abundant in the high‐density, interspecific, GN treatment. Rearing larvae to adulthood under severe food limitation resulted in low survival (<25%) in both resource environments. Approximately 60% of survivors to adulthood were male. Larvae reared in the intraspecific, G treatment had the shortest development time to adulthood and emerged as the smallest adults. These results demonstrate how environmental variation can significantly alter the alpha and beta diversity of free‐living microbes, which in turn can significantly affect host phenotype and critical life history traits, such as development time, size at adulthood, and survival. These findings highlight the importance of considering environmental influences on microbiome diversity to understand and predict host outcomes, offering valuable insights for diverse applications in fields such as ecology, public health, and agriculture.